Calibrationless operation method

ABSTRACT

A method that includes obtaining a sensor reading from a sensor installed inside an underground vault and determining whether the sensor reading is indicative of an alarm state. When the sensor reading is indicative of the alarm state, the method obtains at least one new reading and determines whether the sensor reading includes sensor drift based at least in part on the at least one new reading. The alarm state is established when the sensor reading is determined not to include sensor drift. The sensor drift is removed when the sensor reading is determined to include sensor drift.

BACKGROUND OF THE INVENTION Field of the Invention

The present invention is directed generally to methods of determiningwhether a manhole event has occurred.

Description of the Related Art

Sensor drift refers to a change in a sensor's output signal that isindependent of a property being measured by the sensor. Because ofsensor drift, unless a sensor is calibrated frequently, absolute valuesobtained by that sensor cannot be relied upon. Sensor drift isparticularly acute in sensors that detect analytes and/or particulatesof many different compounds (e.g., H₂, CO₂, CO, O₂, VOCs, H₂S, etc.).Sensor drift is exasperated by a challenging environment, such as theenvironment present inside an underground electrical cable equipmentvault, where high temperatures, substantial diurnal and annualtemperature variations, high humidity, and corrosive chemistry arecommonplace.

Unfortunately, frequent calibration by technicians of sensors presentinside underground vaults is impractical because in busy urban areas,traffic and safety considerations limit or prevent access to theseenvironments. Such sensors are generally calibrated using calibrationgases (“cal-gases”), which possess known concentrations (including zero)of a particular component of interest (analyte) in an inert carrier gas(e.g., nitrogen, argon, and the like). Unfortunately, including suchcal-gases in a system designed for multi-year maintenance-free operationmay be impractical as the required gas quantity may be substantial andthe plumbing required carries its own reliability issues.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a side view of an exemplary manhole event suppression systeminstalled in one of a plurality of manhole vaults interconnected by aplurality of conduits or connections.

FIG. 2 is a perspective view of a manhole cover.

FIG. 3 is an enlarged perspective view of the monitor installed in theunderground vault connected to a System Controller.

FIG. 4 is an illustration of gases entering one of the manhole vaults ofFIG. 1 through a connection to the vault.

FIG. 5 is a bar graph illustrating an accounting of different gaseouscombustion-pyrolysis products of low density polyethylene (“LDPE”)powder taken from Boettner et al, “Combustion Products from theIncineration of Plastics” Michigan University 1973, prepared for theOffice of Research and Development U.S. Environmental Protection Agency,Washington D.C. 20460, EPA-670/2-73-049.

FIG. 6 is a bar graph of a residual gas analyzer (“RGA”) result thatquantifies water evolved from combustion/pyrolysis of rubber compoundstaken from Zhang, Boggs, et al, “The Electro-Chemical Basis of ManholeEvents,” IEEE Electrical Insulation Magazine, Vol. 25, No. 5, 9-10/2009.

FIG. 7A is a flow diagram of a method performed by the monitoring systemof FIG. 1.

FIG. 7B is a flow diagram of a method performed by a monitor of FIG. 1.

FIG. 7C is a first portion of a flow diagram of an evaluate methodperformed by the System Controller of FIG. 1.

FIG. 7D is a second portion of the flow diagram of the evaluate method.

FIG. 7E is a third portion of the flow diagram of the evaluate method.

FIG. 7F is a flow diagram of a highest notification method performed bythe System Controller of FIG. 1.

FIG. 7G is a flow diagram of an intermediate notification methodperformed by the System Controller of FIG. 1.

FIG. 7H is a flow diagram of a lowest notification method performed bythe System Controller of FIG. 1.

FIG. 7I is a flow diagram of a corroborate method performed by theSystem Controller of FIG. 1.

FIG. 7J is a flow diagram of a coordinate method performed by the SystemController of FIG. 1.

FIG. 7K is a flow diagram of a calculate method performed by the SystemController of FIG. 1.

FIG. 7L is a flow diagram of a validate method performed by the SystemController of FIG. 1.

FIG. 7M is a flow diagram of a drift validation process performed by theSystem Controller of FIG. 1.

FIG. 7N is a flow diagram of a persistence validation process performedby the System Controller of FIG. 1.

FIG. 7O is a flow diagram of a desaturate method performed by the SystemController of FIG. 1.

FIG. 7P is a flow diagram of a calibrate method performed by the SystemController of FIG. 1.

FIG. 7Q is a flow diagram of a relate method performed by the SystemController of FIG. 1.

FIG. 7R is a flow diagram of a dilution one test method performed by theSystem Controller of FIG. 1.

FIG. 7S is a flow diagram of a dilution two test method performed by theSystem Controller of FIG. 1.

FIG. 7T is a flow diagram of a dilution one calibration method performedby the System Controller of FIG. 1.

FIG. 7U is a flow diagram of a dilution two calibration method performedby the System Controller of FIG. 1.

FIG. 7V is a flow diagram of a dilution one range method performed bythe System Controller of FIG. 1.

FIG. 7W is a flow diagram of a dilution two range method performed bythe System Controller of FIG. 1.

FIG. 8A is a graph of exemplary sensor readings and a line illustratingsensor drift.

FIG. 8B is a graph of a portion of the exemplary sensor readings of FIG.8A including the line illustrating the sensor drift and linesillustrating upper and lower confidence bounds.

FIG. 9 is a flow diagram of a second method performed by the SystemController of FIG. 1.

FIG. 10 is a flow diagram of a third method performed by the SystemController of FIG. 1.

FIG. 11 is a flow diagram of a fourth method performed by the SystemController of FIG. 1.

FIG. 12 is a flow diagram of a fifth method performed by the SystemController of FIG. 1.

FIG. 13 is a flow diagram of a sixth method performed by the SystemController of FIG. 1.

FIG. 14 is a flow diagram of a seventh method performed by the SystemController of FIG. 1.

FIG. 15 is a flow diagram of an eighth method performed by the SystemController of FIG. 1.

FIG. 16 is an illustration of a network of underground vaults in which afire is occurring in a connection interconnecting two of the vaults.

FIG. 17 is a diagram of a hardware environment and an operatingenvironment in which the System Controller of FIGS. 1 and 3 may beimplemented.

FIG. 18 is a graph illustrating how oxidative decomposition andpyrolysis can create flammable atmospheres inside one or more vaults.

FIG. 19 is a graph illustrating typical evolution of a manhole eventfrom initiation to extinguishment.

Like reference numerals have been used in the figures to identify likecomponents.

DETAILED DESCRIPTION OF THE INVENTION

Underground utilities, such as water, sewer, natural gas, electricity,telephone, cable, and steam, are a common means of delivering theessentials of modern life in a developed society. Referring to FIG. 1,such utilities are often routed through an underground system 100 thatincludes a plurality of substantially identical underground chambers ormanhole vaults 112-116 interconnected by one or more conduits orconnections 118A-118J. The vaults 112-116 may each be configured tohouse equipment 119, such as critical control equipment, monitoringequipment, transformers, and appropriate network connections. As shownin FIG. 1, the vaults 112-116 and the connections 118A-118J arepositioned below a street or sidewalk level (identified as a surface120). In FIG. 1, only the three vaults 112-116 of the system 100 havebeen illustrated. However, the system 100 may include any number ofvaults each substantially similar to one of the vaults 112-116.Similarly, while the ten connections 118A-118J have been illustrated,the system 100 may include any number of connections each substantiallysimilar to one of the connections 118A-118J.

An external atmosphere 122 exists outside the vault 112 (e.g., above thesurface 120) and an internal atmosphere 124 is present inside the vault112. For ease of illustration, air entering the vault 112 from theexternal atmosphere 122 will be described as being fresh air and airfrom the internal atmosphere 124 exiting the vault 112 into the externalatmosphere 122 will be described as being exhaust. Thus, both a flowF_(FA) of fresh air into the vault 112 and a flow F_(E) of exhaust fromthe vault 112 may be present.

A flow F_(C) from one or more of the connections 118A-118J may flow intothe vault 112. One or more gases created by a manhole event may travelinto the vault 112 via one or more of the connection(s) flow F_(C). Whenwater W is present in the vault 112, an evaporation flow F_(V) may bepresent inside the vault 112. The time constant τ (tau) for any givenunderground vault (like the underground vault 112) varies with a waterdepth, the volume of the underground vault 112, and a flow rate of theexhaust flow F_(E).

FIG. 1 illustrates a monitoring system 102 that includes a monitor 126configured to communicate with a System Controller 190 via a wirelessand/or wired connection. The monitor 126 is installed in the undergroundvault 112. The monitor 126 includes or is connected to one or moresensors 128. The monitor 126 includes other components 130 (e.g.,hardware and software) that operate the sensor(s) 128. The components130 may include one or more processors (e.g., a processor 130P) which isconnected to memory 130M that stores instructions 130I. The instructions130I are executable by the processor 130P. By way of a non-limitingexample, the monitor 136 may be implemented as a data logger describedin U.S. patent application Ser. No. 15/476,775, filed on Mar. 31, 2017,and titled SMART SYSTEM FOR MANHOLE EVENT SUPPRESSION SYSTEM, which isincorporated herein by reference in its entirety.

The System Controller 190 may be located remotely or collocated withrespect to the monitor 126. The monitor 136 may be connected to theSystem Controller 190 across one or more networks (not shown).

The exhaust flow F_(E) may be created as least in part by an air movingdevice 132 of a manhole event suppression system 140. The air movingdevice 132 may be configured to blow exhaust (as the flow F_(E)) outthrough one or more of a plurality of through-holes 142 (see FIG. 2)formed in a manhole cover 144 and/or to blow fresh air into the vault112 through one or more of the through-holes 142. In the embodimentillustrated, the air moving device 132 is connected to the manhole cover144 by a first section P1 of a ventilation pipe 148. An inner portion142-E (see FIG. 2) of the through-holes 142 (see FIG. 2) are positionedinside the first section P1 and an outer portion 142-FA (see FIG. 2) ofthe through-holes 142 are positioned outside the first section P1.

The monitor 136 may be positioned in the fresh air flow F_(FA). If theair moving device 132 is configured to exhaust air through the innerportion 142-E (see FIG. 2) of the through-holes 142 (see FIG. 2), themonitor 136 may be attached to an outer surface 150 of the air movingdevice 132 and/or the first section P1. In this manner, the monitor 136is within the fresh air flow F_(FA) as it enters the vault 112. On theother hand, if the air moving device 132 is drawing fresh air in throughthe inner portion 142-E (see FIG. 2) of the through-holes 142 (see FIG.2), the monitor 136 may be attached to an inner surface 146 of the airmoving device 132 and/or the first section P1 so that the monitor 136 isin intimate contact with the fresh air flow F_(FA) entering the outerportion 142-FE (see FIG. 2) of the through-holes 142. In this manner,the monitor 136 is within the fresh air flow F_(FA) as it enters thevault 112. Alternatively, the monitor 136 may be mounted to the vault112 (e.g., on a vault wall). Generally speaking, the fresh air flowF_(FA) is always cooler than the exhaust flow F_(E). Electricalcomponents of the monitor 136 may function better at lower temperatures.By way of a non-limiting example, the monitor 136 may be positionedbetween the fresh air flow F_(FA) and the exhaust flow F_(E) so thatless plumbing is needed to sample both the fresh air flow F_(FA) and theexhaust flow F_(E).

Alternatively, the monitor 136 may be positioned in the exhaust flowF_(E). If the air moving device 132 is configured to exhaust air throughthe inner portion 142-E (see FIG. 2) of the through-holes 142 (see FIG.2), the monitor 136 may be attached to the inner surface 146 of the airmoving device 132 and/or the first section P1. In this manner, themonitor 136 is within the exhaust flow F_(E) before it leaves the vault112. On the other hand, if the air moving device 132 is drawing freshair in through the inner portion 142-E (see FIG. 2) of the through-holes142 (see FIG. 2), the monitor 136 may be attached to the outer surface150 of the air moving device 132 and/or the first section P1 so that themonitor 136 is in intimate contact with the exhaust flow F_(E) exitingthrough the outer portion 142-FE (see FIG. 2) of the through-holes 142.In this manner, the monitor 136 is within the exhaust flow F_(E) beforeit leaves the vault 112. Alternatively, the monitor 136 may be mountedto the vault 112 (e.g., on a vault wall).

Referring to FIG. 3, the sensor(s) 128 may include a water level sensor214 and at least one fire detection sensor 216 together with hardwareand software configured to operate the sensors 214 and 216. The firedetection sensor(s) 216 may include a temperature sensor, a humiditysensor, a visible light camera, an infra-red camera, a motion sensor, aparticulate sensor, a smoke sensor or detector, and a chemicalconcentration sensor. Examples of chemical concentration sensors thatmay be used to implement one or more of the fire detection sensor(s) 216include sensors configured to detect O₂, CO₂, CO, H₂, VOCs, NO, NO₂,particulates, and O₃. By way of non-limiting examples, the firedetection sensor(s) 216 may detect one or more of the followingconditions, which indicate a corresponding fire or flammable gasaccumulation (“FGA”) specified in parenthesis:

-   -   i. CO₂ is elevated (oxidative decomposition);    -   ii. CO is elevated (pyrolysis);    -   iii. VOCs are elevated (pyrolysis or FGA);    -   iv. H₂ is elevated (pyrolysis);    -   v. NO is elevated (evidence of plasma/electrical discharge or        high temperature oxidative decomposition);    -   vi. NO₂ is elevated (evidence of plasma/electrical discharge or        high temperature oxidative decomposition);    -   vii. O₃ is elevated (evidence of plasma/electrical discharge or        high temperature oxidative decomposition);    -   viii. H₂O (absolute humidity) is elevated (oxidative        decomposition);    -   ix. O₂ is depressed (dilution by i-vii, and consumption by        oxidative decomposition and partial pyrolysis);    -   x. Temperature is elevated (oxidative decomposition);    -   xi. Particulates are elevated (any or all oxidative        decomposition, pyrolysis, plasma/electrical discharge); and    -   xii. Smoke is observed in visual or infra-red wavelengths by        pattern recognition algorithms or by motion detection (any or        all oxidative decomposition, pyrolysis, plasma/electrical        discharge).

Referring to FIG. 1, the equipment 119 located in the underground vault112 may include and/or be connected to cables 160. Equipment (like theequipment 119) may be located in other vaults (e.g., the vaults 114 and116) connected to the vault 112. The electrical equipment 119 may causemanhole events. Manhole events include both minor incidents (such assmoke or small fires) and/or major events (such as sustained fires andexplosions). The manhole event suppression system 140 may be installedin the underground vault 112 to help prevent manhole events. The monitor136 is illustrated integral with the manhole event suppression system140, but the monitor 136 may also be independent of the manhole eventsuppression system 140.

As mentioned above, the air moving device 132 of the manhole eventsuppression system 140 is configured to exchange air between theexternal atmosphere 122 outside the vault 112 and the internalatmosphere 124 inside the vault 112. For example, the air moving device132 of the manhole event suppression system 140 may blow fresh air fromthe external atmosphere 122 into the internal atmosphere 124 and/or mayexhaust air from the internal atmosphere 124 into the externalatmosphere 122. Such air exchange may be referred to as activeventilation. By way of non-limiting examples, the manhole eventsuppression system 140 may be implemented in accordance with any of theventilation systems described in U.S. patent application Ser. No.15/084,321 filed on Mar. 29, 2016 (titled VENTILATION SYSTEM FOR MANHOLEVAULT), U.S. patent application Ser. No. 15/173,633, filed Jun. 4, 2016(titled SYSTEMS FOR CIRCULATING AIR INSIDE A MANHOLE VAULT), and/or U.S.patent application Ser. No. 15/476,775, filed on Mar. 31, 2017 (titledSMART SYSTEM FOR MANHOLE EVENT SUPPRESSION SYSTEM). Each of theaforementioned patent applications is incorporated herein by referencein its entirety.

The internal atmosphere 124 may include an undesired (and potentiallydangerous) gaseous composition 164. The gaseous composition 164 may benon-uniformly distributed within an interior 166 of the vault 112. Forexample, the gaseous composition 164 may be adjacent or near a floor 168of the vault 112.

A sensor's output signal or readings may be inaccurate for a number ofreasons, including sensor drift, noise, and the like. Sensor drift is achange in a sensor's output signal or readings that occurs over time andis independent of the thing (e.g., concentration of an analyte) beingmeasured. Noise is random variations in the output signal or readings ofa sensor. Variations caused by sensor drift and/or non-drift variations(e.g., noise) will be referred to as inconsequential variations andvariations caused by a manhole event will be referred to asconsequential variations. At least some of the inconsequentialvariations can be removed by calibrating the sensor. Unfortunately, itis not always practical to calibrate a sensor, such as one or more ofthe fire detection sensor(s) 216 installed in the underground vault 112.Therefore, a process referred to herein as “Calibrationless Operation,”described below, may be implemented for one or more of the firedetection sensor(s) 216.

The useful life of a sensor may be extended using CalibrationlessOperation. For example, a sensor package may use CalibrationlessOperation to extend the life of one or more of its sensors.Calibrationless Operation involves the statistical filtering of sensordrift, noise, and the like. Sensor drift occurs slowly and independentlyof random sensor noise. Sensor drift is generally only significant overa period of days. Events (such as fires or natural gas leaks) thatincrease analytes of interest, (such as VOCs, H₂, CO, H₂O (relativehumidity), NO, NO₂, O₃, and/or CO₂), and sometimes cause correspondingdecreases in other analytes, such as O₂, tend to exhibit much lower timeconstants—measureable in minutes or hours. Thus, increases in analytesof interest that occur within a short time period are typically notcaused by sensor drift and are much more likely to indicate a manholeevent is occurring.

Calibrationless Operation models past behavior of a sensor to identifydrift and/or noise and avoids acting upon identified drift and/or noise.A purely statistical approach to identifying drift and/or noise presentsa direct trade-off between identifying false positives and falsenegatives. That is, a practitioner can set a very high bar for detectinga dangerous gas, which would reduce the number of false positives, butmust as a result accept a higher probability of false negatives. Toovercome this tradeoff, Calibrationless Operation deploys at least oneof the following three corroborating techniques: confirmatorymeasurement(s), complementary corroboration, and active dilution.

Confirmatory Measurement(s)

When a suspected alarm condition is detected by a sensor, at least oneconfirmatory measurement is made quickly after the detection. Forexample, multiple confirmatory measurements may be made in rapidsuccession to test for random variations (noise). Such confirmatorymeasurement(s) may be collected from the same sensor (a first sensor) orat least one corroborating sensor. A corroborating sensor is not thefirst sensor, but may include an identical redundant sensor, a similarsensor, and/or a complimentary sensor. Similar sensors measure the samething as the first sensor, but using different properties. For example,CO can be measured electrochemically or by using infrared. Identicalredundant sensors may use the same measuring technology as the firstsensor but may be scaled differently and operated in different ranges.Complimentary sensors measure different properties from the first sensorbut may be used to reach, at least in part, the same conclusion as thefirst sensor. Corroborating sensors may be located in the same controlbox as the first sensor, in a different control box in the same vault asthe first sensor, or in one or more adjacent vaults.

Complementary Corroboration

Where fires are suspected (not just the accumulation of VOCs or H₂S)corroborating sensors may provide the corroboration to effectuate analarm condition. As mentioned above, such corroborating sensors may belocated in the same control box as the first sensor, in a differentcontrol box in the same vault as the first sensor, or in one or moreadjacent vaults.

As mentioned above, complimentary sensors measure different propertiesfrom the first sensor but may be used to reach, at least in part, thesame conclusion as the first sensor. Thus, whether two or more sensorsare complimentary depends upon the conclusion being reached. Forexample, when trying to determine if a fire is present, a CO sensor iscomplimentary to a CO₂ sensor because carbon monoxide is created in anycarbon dioxide (CO₂) generating fire. By way of another non-limitingexample, when trying to determine if a fire is present, a temperaturesensor is complimentary to a CO₂ sensor because the temperature sensormay detect an increase in temperature at the same time the CO₂ sensordetects an increase in CO₂. Corroborating sensors can be collocated in asensor package within a single vault, located in a least one othersensor package within the single vault, and/or located in adjacentvaults.

Table A lists gaseous compounds likely to be encountered in a manholesorted from lowest to highest density along with their lower explosivelimits (“LEL”) and upper explosive limits (“UEL”) for flammablematerials. Boettner et al, “Combustion Products from the Incineration ofPlastics,” Michigan University 1973, prepared for the Office of Researchand Development U.S. Environmental Protection Agency, Washington D.C.20460. EPA-670/2-73-049; “Gas Data Book,” 7th Ed. 2001 by Matheson GasProducts; and “Flammability Characteristics of Combustible Gases andVapors,” 1965, U.S. Department of Interior, Bureau of Mines Bulletin627. A leftmost column lists classes based on the compound's density:lighter-than-air (“LTA”), similar-to-air (“STA”), and heavier-than-air(“HTA”). Carbon, which is listed on the last row at the bottom of TableA, is a special case. Carbon is a solid and has a density over threeorders of magnitude higher than air, but has an outsized contribution tomany manhole explosions.

TABLE A Density Density (Kg/m³ (SG Class Compound @STP) @STP) LEL (% v)UEL (% v) LTA Hydrogen 0.09 0.07 4.0 75.0 STA Methane 0.72 0.56 4.4 17.0STA Water vapor 0.80 0.63 Non- Non-flammable flammable STA Acetylene1.15 0.90 2.5 100.0 STA Carbon 1.25 0.98 12.5 74.2 Monoxide STA Nitrogen1.25 0.98 Non- Non-flammable flammable STA Ethylene 1.26 0.98 2.7 36.0STA Ethane 1.26 0.99 3.0 12.4 STA Air 1.28 1.00 Oxidizer Oxidizer STAHydrogen 1.36 1.06 4.0 44.0 sulfide STA Oxygen 1.43 1.12 OxidizerOxidizer STA Propylene 1.74 1.36 2.4 11.0 STA Propane 1.88 1.47 2.1 9.5STA Carbon dioxide 1.98 1.67 Non- Non-flammable flammable HTA 1-butene2.48 1.94 1.6 10.0 HTA trans-2-butene 2.50 1.95 1.7 9.7 HTA cis-2-butene2.50 1.95 1.7 9.7 HTA Butane 2.57 2.01 1.8 8.4 HTA 1,3-pentadiene 3.012.35 2.0 8.3 HTA 1-pentene 3.07 2.40 1.4 8.7 HTA Pentane 3.19 2.49 1.47.8 HTA 1-hexene 3.84 3.00 1.2 6.9 HTA 2-hexene 3.84 3.00 1.2 6.9 HTACarbon 2260 1766 Combustible Dust

The fourth column above, lists a specific gravity (“SG”) for each of thegaseous compounds.

FIG. 4 illustrates each of three classes of flammable vapors enteringthe vault 112 from the exemplary connection 118E (e.g., a duct). Anarrow 170 illustrates one or more LTA compound, an arrow 172 illustratesone or more STA compound, and an arrow 174 illustrates one or more HTAcompound entering the vault 112. FIG. 4 also includes LTA zones ZL1-ZL3,a central STA zone ZS, and HTA zones ZH1-ZH3. The LTA compound(s) maygravitationally striate into the three LTA zones ZL1-ZL3 and the HTAcompound(s) may gravitationally striate into the three HTA zonesZH1-ZH3. The zones ZL2 and ZH2 are combustion zones where each flammablecomponent is above its lower explosive limit (“LEL”), but below itsupper explosive limit (“UEL”). The zones ZL1 and ZL3 are below and abovethe combustion zone ZL2, respectively, and the zones ZH1 and ZH3 areabove and below the combustion zone ZH2, respectively. In each of thezones ZL3 and ZH3, there is not enough oxygen present (i.e., the mixtureis too rich; the concentration is >UEL) for the flammable component(s)to burn. In each of the zones ZL1 and ZH1, there is not enough fuelpresent (i.e., the mixture is too lean; the concentration is <LEL) forthe flammable component(s) to burn. The STA compound(s) do not striate.Instead, they intermix with the air. While there are dynamicconcentration gradients, the STA compound(s) will equilibrate toward auniform concentration throughout the central STA zone ZS.

Once outside a specific gravity range of about 0.5 to about 2.0 andabsent convective air circulation, gases may separate into the striatedlayers illustrated in FIG. 4. The HTA compound(s) tend to sink to thebottom of a structure (e.g., the vault 112). The LTA compound(s) tend tofloat to the top of the structure. The STA compound(s) fill centralportions between the top and bottom of the volume not filled by the LTAand HTA compound(s). Any gravitational striation is dynamic. Dynamicconsiderations include the following: new gases that may enter or exitfrom the connection(s) flow F_(C), gases that diffuse or leak from or tothe vault 112, and gases that diffuse from one zone to an adjacent zonedriven by concentration gradients against gravitational striation.

An explosion occurs when a gas or plasma expands at a rate that is equalto or faster than the speed of sound. Fire is a complex set of physicaland chemical reactions. Almost all of the plastics, polymers, andrubbers that the electrical industry uses are dominated by a singlerepeating polymeric unit. A non-limiting example of such a polymericunit is methylene, which includes a single carbon atom, two hydrogenatoms, and two unpaired electrons represented thusly: —CH₂—. There islittle difference between all of the different types of polyethylene(“PE”) including high molecular weight PE (“HMWPE”), cross-linked PE(“XLPE”), Linear-Low Density PE (“LLDPE”), Low Density PE (“LDPE”), HighDensity PE (“HDPE”) and Tree-Retardant cross-linked PE (“TRXLPE”) whenit comes to their burn chemistry.

If electricity is not involved, there are only two kinds of burning:oxidative decomposition and pyrolysis. When electrical discharges areinvolved, a third kind of burning, plasmatization (and its reverse), maybe present. These three kinds of burning usually occur in the followingorder: plasmatization, pyrolysis, and oxidative decomposition.

Oxidative decomposition is represented by Equation 1 below and is whatmost people think of when they contemplate the chemistry of fire.

2—CH₂—+3O₂→CO₂+2H₂O   (1)

Pyrolysis is thermal anaerobic (in the absence of oxygen) decompositionof methylene. Pyrolysis may be represented by Equation 2 below.

α-CH₂—→βC+γH₂+OC_(n)H_(m)   (2)

In Equation 2 above, Greek letters represent integers that satisfy anatom balance that varies greatly depending on conditions. The variable“n” represents a small integer and the variable “m” represents anumerical value between 1 and 3 times the value of the variable “n.”

FIG. 5 is an accounting of different gaseous combustion-pyrolysisproducts of low density polyethylene (“LDPE”) powder taken from Boettneret al, “Combustion Products from the Incineration of Plastics” MichiganUniversity 1973, prepared for the Office of Research and DevelopmentU.S. Environmental Protection Agency, Washington D.C. 20460,EPA-670/2-73-049. Non-definitive compound designations listed on they-axis indicate that more than a single species is included. Forexample, C₂H₄₋₆ includes ethane (C₂H₆) and ethylene (C₂H₄). Elementalcarbon, water, and hydrogen were not measured by the researchers and arenot shown in FIG. 5.

FIG. 6 is a residual gas analyzer (“RGA”) result that quantifies waterevolved from combustion/pyrolysis of rubber compounds taken from Zhang,Boggs, et al, “The Electro-Chemical Basis of Manhole Events,” IEEEElectrical Insulation Magazine, Vol. 25, No. 5, 9-10/2009. RGA suffersfrom an inability to resolve CO if N₂ is present as well as to resolveelemental carbon. Note that the x-axis of FIG. 6 is not the same as FIG.5. Here the abundance of each gas is a normalized volume. Differencesbetween FIG. 6 and FIG. 5 include: fuel (which is SBR/EPR insulation inFIG. 6), temperature conditions, oxygen concentration, and theanalytical technique. Additionally, the analytical technique employed toobtain the data of FIG. 5 was blind to water vapor and the techniqueused to obtain the data of FIG. 6 was blind to carbon monoxide whennitrogen was present. Both analytical techniques are blind to elementalcarbon.

The data of FIGS. 5 and 6 are reconciled by acknowledging that neitherrepresentation is perfect, but both yield similar and complimentaryresults.

FIGS. 5 and 6 show a relative abundance of the compounds that are formedby pyrolysis. Most likely, every compound that could be formed isformed, but some compounds are simply present in a concentration that istoo low to be identified. A polymer, like XLPE, does not burn directly.Instead, the polymer undergoes pyrolysis when it is heated and thusgenerates gases like those implied by Equation 2. After pyrolysisoccurs, the resulting gaseous compounds can mix with oxygen and undergooxidative decomposition. Equation 1 does a fine job of representing thenet reaction if there is plenty of oxygen present. Incomplete combustionoccurs when there is not enough oxygen present to produce the carbondioxide and water of Equation 1. Such incomplete combustion is partiallyrepresented by Equation 3 below.

3-CH₂—+2O₂→C+CO+CO₂+H₂+2H₂O   (3)

Equation 3 properly balances for the combustion-pyrolysis case wherethere are precisely two oxygen molecules for every three methyleneunits. The fuel and the oxygen are not well mixed in duct-manholescenarios. Less oxygen generates more carbon (the black in black smoke),more carbon monoxide, and more hydrogen at the expense of carbon dioxideand water. FIGS. 5 and 6 display the messy reality that occurs whenoxidative decomposition, pyrolysis, and incomplete combustion occursimultaneously as represented by Equations 1-3.

Turning now to the third kind of burning, namely plasmatization and itsreverse, an electrical arc has a temperature of between 16,900° K(30,000° F.) and 28,000° K (50,000° F.). At these temperatures, thechemistry is entirely different from what is described above. Every atomis torn from every other atom and many electrons are ripped from theirnuclei. Equation 4 below shows the net result of these first two steps.

—CH₂—+N₂+O₂→C^(γ+)+2H²+2N^(v+)+2O^(o+)+εe⁻  (4)

where . . .

ε=γ+2+2v+2o   (5)

The precise charge of every atom on the right side of Equation 4 aboveis dependent on the temperature of the plasma and hence the value ofepsilon. The number of free electrons balances the positive charges asshown by Equation 5 above. Hydrogen has only a single electron tocontribute to the plasma cloud. Carbon, nitrogen, and oxygen have 6, 7,and 8 electrons respectively. Each incremental electron is moredifficult to strip than the previous electron and requires a highertemperature to do so. Other atom(s) and/or molecule(s) that is/areconsumed in the arc flash are not shown in FIG. 6. Clay fillers in EPRinsulation, aluminum and copper conductors and neutrals, water, carbonblack, and anything else nearby are broken into their respectiveconstituent atoms and electrons are stripped from their outermostorbitals.

Plasma cannot burn. The atoms are too hot to react with each other.

Three lessons may be gained from the three kinds of burning. The firstlesson involves burning and explosion. All burning involves bothpyrolysis and combustion as a minimum. Where combustion predominates,smoke is clear or white (water vapor). Where pyrolysis predominates,smoke is black (carbon) and includes substantial carbon monoxide. Whenelectricity is involved, there is some level of plasma formation. For aprimary cable failure where the voltage to ground is at least severalthousand volts, the plasma may be the predominant route, but there willalways be some combustion (unless the environment is completelyanaerobic) and some pyrolysis. For secondary cable failures where thevoltage to ground is typically just several hundred volts, plasma ispresent, but at a subdued level compared to a brief high current primaryfault. Secondary “faults” can persist for days and while the plasma,pyrolysis, and combustion proceed at a slow pace, the accumulation offlammable gases and solid carbon in confined spaces together with ampletime to mix with atmospheric oxygen may create the conditions for thelargest possible chemical explosions. Sun, Ma and Boggs, “Initiation ofa Typical Network Secondary Manhole Event,” IEEE Electrical InsulationMagazine, v.31.n.3, May/June 2015.

The second lesson involves carbon monoxide. Carbon monoxide is thelargest contributor to secondary network explosions. Table A above showscarbon monoxide is an STA compound with a wide flammable range spanning12.5%_(v) to 74.2%_(v). Further, as shown in FIGS. 5 and 6, carbonmonoxide is one of the most abundant gases created in the conditionslikely to be encountered in a secondary network. While we cannot ignorethe hydrocarbons, they are not as abundant and hence are not of thegreatest concern.

The third lesson involves carbon. Carbon is the second largestcontributor to secondary network explosions. As carbon plasma cools, itremains a gas until the temperature reaches about 4,098° K (6,917° F.)where it becomes a liquid. The liquid state of carbon does not last longas it solidifies at about 3,823° K (6,422° F.). After solidifying,atomic carbon has a very high surface energy as a result of its fourunpaired electrons. Adjacent carbon atoms tend to agglomerate into dustparticles several microns in diameter. The agglomerates have largesurface areas and high porosity.

Even though the density of the solid phase of carbon is over 1,700 timesthe density of air, the agglomerates are predominantly gaseous voidsfilled with the very same gases that surround the particle. As aconsequence, the bulk density places carbon agglomerates alongside HTAgases. The slightest convection currents keep the agglomerates aloft.These carbon agglomerates are what make black smoke black. Thus,although solid carbon is not gas, solid carbon agglomerates act asthough they are a gas, and when the terms “gas,” “gases,” or “gaseous”are used herein, carbon agglomerates are included.

When mixed with air, these particles can be ignited and participate in adust explosion. A hetero-explosion occurs when these particles are mixedwith air, carbon monoxide, hydrogen, and smaller amounts of hydrocarbongases and ignited. The yield of the hetero-explosion depends upon one ormore of the following:

-   -   1. quantities of each fuel;    -   2. relative quantity of oxygen to each fuel;    -   3. relative quantities of gaseous components that retard        combustion most notably including, nitrogen, carbon dioxide, and        water vapor, the latter two being products of oxidative        combustion;    -   4. uniformity of how the aforementioned items 1, 2 and 3 are        mixed (e.g., better mixing yields more explosive energy); and    -   5. location of the ignition source relative to the center of        mass of the cloud delineated by explosive limit concentration        boundaries.

Active Dilution

Referring to FIG. 3, as mentioned above, the manhole event suppressionsystem 140 may ventilate the underground vault 112. Thus, the manholeevent suppression system 140 may be used to implement variable activeventilation. However, such ventilation may occur by an alternate means.

Variable active ventilation is referred to as dilution of the firsttype. Dilution of the first type is accomplished by changing an overallrate of atmospheric turnover in the underground vault 112. For example,doubling of the exhaust rate approximately halves a concentration ofthose gases that are rare in the internal atmosphere 124, but areentering the underground vault 112 from a fire event. Converselydoubling of the exhaust rate increases the concentration in the internalatmosphere 124 of those gases that are abundant in the externalatmosphere 122, namely oxygen and nitrogen. It is preferable to be ableto flexibly control the flow rate and direction scalably from zero to atleast one hundred percent and zero to minus one hundred percent of anair movement device, but another alternative is to have two or morepreset flows including for example any two values referred to as off,low, medium and high. Yet another alternative is to turn an air movementdevice on and off over periodic time spans (e.g. fan 100% on for 30seconds, fan 0% for 30 seconds yields approximately a 50% flow over a 60second period). In the event of an emergency or potentially pendingemergency, it is preferred to be able to run the air movement deviceabove its 100% design speed.

As a practical matter, a maximum exhaust rate during routine (ornon-emergency) operation is constrained by public perception. A jet-likeexhaust rate would be noisy and considered a nuisance. On the otherhand, noise might be a desirable feature when preventing an imminentexplosion. No matter what the maximum exhaust rate may be, there arecircumstances where dilution of the first type will simply be unable toprovide sufficient dilution to avoid the occurrence of a manhole event(e.g., a fire and/or explosion). In other words, enough of the undesiredgaseous composition 164 (see FIG. 1) cannot be exhausted from theunderground vault 112 (e.g., via a high duct flow event) to providereadings from the fire detection sensor(s) 216 that are within desiredsensor range(s) and/or prevent a buildup of flammable gases approachingan effective lower explosive limit. Put another way, an activeventilation system (e.g., the manhole event suppression system 140) canbe overwhelmed by a large influx of flammable gas(es).

Direct sample dilution is referred to as dilution of the second type.Dilution of the second type refers to fresh air (from the externalatmosphere 122) intermixing with a sample portion of the exhaust thatpasses by the fire detection sensor(s) 216. Thus, dilution of the secondtype is not constrained by the range of possible exhaust rates. However,dilution of the second type does nothing to change the internalatmosphere 124 inside the underground vault 112. When it is desirable todilute potentially explosive gases within the underground vault 112,dilution of the first type may be used to exhaust the internalatmosphere 124 up to the maximum exhaust rate. The greatest flexibilityis achieved by the combination of both dilution types.

While dilution of the first type is limited to 0% to 100% of the maximumexhaust rate (or perhaps in emergency conditions a value greater than100%), dilution of the second type is infinitely scalable. For example,a sample air moving device 178 may be used to move fresh air from theexternal atmosphere 122 past the fire detection sensor(s) 216. Anexhausted air moving device 179 may be used to move an exhausted gasmixture from the exhaust flow F_(E) past the fire detection sensor(s)216. In such embodiments, one end of a tube 180 or similar conveyanceconduit may be placed in fluid communication with the externalatmosphere 122 or the fresh air flow F_(FA). Similarly, one end of atube 182 or similar conveyance conduit may be placed in fluidcommunication with the exhaust flow F_(E). The other end of the tube 180may deliver a flow F_(D2) of fresh air to be mixed with a portion of theexhaust flow F_(E) conducted by the tube 182, which is illustrated as aflow F_(PE). The flow F_(PE) mixes with the flow F_(D2) in a controlledintermix ratio (“IMR”) that may range from zero to infinity. The flowrates of the flows F_(D2) and F_(PE) may be controlled by the air movingdevices 178 and 179, which may each be implemented using any of a largevariety of means well known in the art. By way of a non-limitingexample, the air moving devices 178 and 179 may be implemented as a pairof gas pumps and micro-flow control valves actuated by a pair ofProportional-Integral-Derivative (“PID”) controllers. The set-points ofthe PID controllers may be determined by the monitor 136 and/or theSystem Controller 190.

By way of another non-limiting example, the sample air moving devices178 and 179 may be implemented as a pair of positive displacement pumpsused to obtain the IMR established by the System Controller 190. The IMRis a ratio of a first volume of exhaust air to a second volume of freshair. The IMR may be determined using relative displacements of thepositive displacement pumps and their cycle frequencies. For example, ifa first positive displacement pump is drawing the flow F_(PE), has avolume of 10 ml/cycle, and is operating at 10 cycles per minute, thefirst positive displacement pump pumps 100 ml of exhaust air everyminute. If a second positive displacement pump is drawing the flowF_(D2), has a volume of 5 ml/cycle, and is operating at 10 cycles perminute, the second positive displacement pump pumps 50 ml of fresh airevery minute. Thus, the IMR would be two-to-one (or 100 ml to 50 ml perminute). If the first positive displacement pump was increased to 30cycles per minute and the second positive displacement pump remained at10 cycles per minute, the IMR would be six-to-one (or 300 ml to 50 mlper minute).

The IMR is set by the System Controller 190 to achieve three fundamentalends: (1) to determine at least one analyte of interest is nearing alimit of detectability; (2) to validate that at least one of the firedetection sensor(s) 216 in an alarm state is not in that state becauseof drift; and (3) to calibrate at least one of the fire detectionsensor(s) 216. If an analyte is at, near, or above its upper limit ofdetectability for the relevant sensor(s), the IMR can be reduced to avalue as low as zero. If an analyte is at, near, or below its lowerlimit of detectability for the relevant sensor(s), the IMR can beincreased to any value, even approaching infinity, to allow each of therelevant sensor(s) to operate within its acceptable or optimal range.There may be circumstances where at least one first sensor would benefitfrom a low IMR, while a least one second sensor would benefit from ahigh IMR. In such circumstances, the System Controller 190 may alternatethe IMR to get valid sensor readings from at least the first and secondsensors. In circumstances where the output from the first sensor is morecritical to a current condition than the output from the second sensor,the System Controller 190 may choose an IMR that keeps the more criticalsensor(s) operating in an appropriate range.

Validation is a quick check for sensor drift. Because drift isindependent of dilution and the IMR, any significant perturbation of theIMR will either quickly manifest itself by a change in the sensor outputof the analyte or not.

The former indicates the perturbation is not caused by sensor drift. Onthe other hand, the later indicates the perturbation is caused at leastin part by sensor drift. Since the output of the sensor of interest ismoving either to greater or lesser values, the IMR may be increased ordecreased to exasperate rather than mitigate that movement. For example,if a CO sensor detects that the CO is increasing, which suggests thatcombustion has started, the System Controller 190 may increase the IMR(thus, decreasing fresh air). After the IMR is increased, if the outputof the CO sensor merely drifts upwards, this perturbation would have nodiscernable impact. On the other hand, if there is a fire, the COreading would increase by a significant amount. A threshold value may beused to determine whether the increase is significant. Thus, the SystemController 190 may instruct the sample air moving devices 178 and 179 tomake meaningful changes to the IMR to assure that the impact on sensoroutput is well above a noise level for the sensor. The slope (which isthe change in analyte concentration divided by the time interval) can beapplied to scale a change in the IMR that will be easy to discern fromthe historical slope. The noise level for each of the fire detectionsensor(s) 216 is continuously calculated and consequential variationsare easily recognized as those sensor readings above the noise level.Perturbations of the IMR can be repeated and reversed as many times asrequired until the System Controller 190 has enough statisticalconfidence in each of the relevant sensor(s) to take action based on itsoutput.

The third form is direct calibration. Using direct calibration the IMRis set to zero (i.e., 100% fresh air is fed to the fire detectionsensor(s) 216) and either assumed atmospheric levels or measuredatmospheric levels are used to calibrate the fire detection sensor(s)216. For example CO₂ is generally about 400 ppm in the troposphere.Therefore, 400 ppm may be used as an assumed atmospheric level of CO₂.Thus, those of the fire detection sensor(s) 216 configured to measureCO₂ concentration may be calibrated to measure 400 ppm when the IMR isset to zero. Alternatively, other sensors that are not inside the vault112 and can be directly calibrated using well-known and/or conventionalmethods can provide an actual or measured CO₂ level. In this manner,those of the fire detection sensor(s) 216 configured to measure CO₂concentration may be calibrated to the measured CO₂ level when the IMRis set to zero. The measured CO₂ level is provided to the SystemController 190 via a wired or wireless data connection (not shown).

Dilution of both the first and second types are referred to as “activedilution.” The time constant (τ tau) of dilution of the first type isquite long, generally at least several minutes. On the other hand, thetime constant (τ tau) of dilution of the second type is quite short,generally on the order of less than 60 seconds.

Sensor drift is independent of active dilution. This independence fromdilution means that it is possible to confirm drift when CalibrationlessOperation uses active dilution.

Since drift is independent of dilution, actively altering the dilutionrate can test the hypothesis that the alarm condition is the result of asudden drift. A negative result to this hypothesis confirms theconcentration change is bona fide.

Calibrationless Operation

FIG. 7A is a flow diagram of a method 200-A that implementsCalibrationless Operation of the fire detection sensor(s) 216 installedinside the underground vault 112 (see FIG. 1). The method 200-A isperformed by the monitoring system 102.

As mentioned above, the sensor(s) 128 may include the water level sensor214 and the fire detection sensor(s) 216. The Calibrationless Operationimplemented by the method 200-A may not be applicable to the water levelsensor 214. In such embodiments, the method 200-A may be performed withrespect to only the fire detection sensor(s) 216. For ease ofillustration, the method 200-A will be described as being performed withrespect to only a sensor 128A (see FIG. 3), which is one of the firedetection sensor(s) 216. However, the fire detection sensor(s) 216 mayinclude any number of sensors and the method 200-A may be performed withrespect to any number of sensors.

The System Controller 190 (see FIGS. 1 and 3) records a mode associatedwith the sensor 128A (see FIG. 3) each time block 215-C (see FIG. 7C) isperformed for the sensor 128A in an evaluate method 200-C (see FIG. 7C).Thus, a number of mode values may be stored for the sensor 128A (seeFIG. 3). For example, the System Controller 190 (see FIGS. 1 and 3)stores a current mode_(t) and a previous mode_(t−1) for the sensor 128A(see FIG. 3). The previous mode_(t−1) stores the mode value immediatelypreceding the current mode_(t). In first block 210-A, the SystemController 190 (see FIGS. 1 and 3) sets both the current mode_(t) andthe previous mode_(t−1) of the sensor 128A (see FIG. 3) equal toINITIALIZE.

In block 220-A, the monitor 136 sends a request to the System Controller190 (see FIGS. 1 and 3) for flag values and system parameters. Inalternative embodiments, the System Controller 190 may push the flagvalues and system parameters to the monitor 126. In such embodiments,the block 220-A may be omitted.

In block 230-A, the System Controller 190 sends the flag values andsystem parameters to the monitor 126. For example, the System Controller190 sends the current mode_(t) is equal to INITIALIZE to the monitor126. The monitor 136 stores these values in the memory 130M.

The flag values may include the current mode_(t), the previousmode_(t−1), a Trigger Condition (“TC”), a trip state (“TS”), a reporttime, an event type indicator, and an Alarm State (“AS”) associated witheach of the fire detection sensor(s) 216 (e.g., the sensor 128Aillustrated in FIG. 3). The current mode_(t) and the previous mode_(t−1)may each be set to one of a plurality of mode values. By way of anon-limiting example, the plurality of mode values may includeINITIALIZE, ROUTINE, TRIPPED, CALIBRATE1, CALIBRATE2, DRIFT1, andDRIFT2.

The TC may be set to one of a plurality of Trigger Condition values. Byway of a non-limiting example, the TC may be set to a triggered value(e.g., one) or a not triggered value (e.g., zero). Non-limitingillustrative examples of the kinds of events that might trigger alarmcondition(s) include the following:

-   -   1. Oxidative Decomposition (“OD”);    -   2. Pyrolysis (“PY”);    -   3. Plasmatization (“PL”); and    -   4. Flammable gas accumulation (“FA”).        Two or more of the above alarm condition(s) may be combined or        collapsed for user simplicity. For example, OD, PY, and PL may        be combined into a single alarm condition called Fire (“FI”).

The TS may be set to one of a plurality of Trip State values. By way ofa non-limiting example, the TS may be set to a not tripped value (e.g.,zero), a single trip value (e.g., one), or a consecutively tripped value(e.g., two). The not tripped value (e.g., zero) indicates the sensor hasnot detected any potential alarm conditions (or no-event operation). Thesingle trip value (e.g., one) indicates a first time that the singlesensor 128A (see FIG. 3) has detected a single potential alarmcondition. The consecutively tripped value (e.g., two) indicates thatthe sensor 128A (see FIG. 3) has repeatedly detected the same potentialalarm condition.

The event type indicator stores one of a plurality of event type values.By way of a non-limiting example, the event type values may include a noevent value, a combustion value, and an FGA (i.e., flammable gasaccumulation) value.

The AS stores an alarm state value and an associated time for each ofthe fire detection sensor(s) 216 (e.g., the sensor 128A illustrated inFIG. 3). The alarm state value may each store one of a plurality ofalarm state values. By way of a non-limiting example, the alarm statevalues may include a low value, an intermediate value, and a high value.

The report time may be set to one of a plurality of report time values.By way of a non-limiting example, the report time may be set to aroutine value (e.g., 15 minutes) or a non-routine value (e.g., 30seconds).

The system parameters may include a baseline C₀ for each of the firedetection sensor(s) 216 (e.g., the sensor 128A illustrated in FIG. 3), abaseline time for each of the fire detection sensor(s) 216, and a fanspeed for an air moving device 132, an air moving device 178, and/or anair moving device 179. The fan speed may be set to one of a plurality offan speed values. By way of a non-limiting example, the fan speed may beset to off, full (or 100%), and a numeric value corresponding to anumber of consecutive seconds that the fan is on over a predeterminedtime period (e.g., 60 seconds).

In block 240-A, the monitor 136 performs a method 200-B (see FIG. 7B).Thus, the instructions 130I, when executed by the processor 130P, areconfigured to instruct the processor 130P to perform the method 200-B(see FIG. 7B). The instructions 130I, when executed by the processor130P, may be configured to instruct the processor 130P to perform block220-A, when present, and block 230-A.

In block 250-A, the System Controller 190 performs the evaluate method200-C (see FIGS. 7C-7E).

Then, the method 200-A terminates.

FIG. 7B is a flow diagram of the method 200-B performed by the monitor126. For ease of illustration, the fire detection sensor(s) 216 will bedescribed as including only the sensor 128A (see FIG. 3). Thus, themethod 200-B will be described as being performed with respect to onlythe sensor 128A (see FIG. 3). However, the fire detection sensor(s) 216may include any number of sensors and the method 200-B may be performedwith respect to any number of sensors.

In first block 205-B, the monitor 136 polls the sensor 128A (see FIG. 3)for a sensor value C′ and adds the sensor value C′ to a collection ofsensor values collected from the sensor 128A. By way of a non-limitingexample, the monitor 136 may poll the sensor 128A for a new sensor valueC′ periodically with a frequency of about 1 Hz.

Then, in decision block 210-B, the monitor 136 determines whether thecurrent mode_(t) is equal to INITIALIZE.

When the current mode_(t) is equal to INITIALIZE, in block 215-B, themonitor 136 sets a corrected value C equal to the sensor value C′collected in block 205-B and adds the corrected value C to a collectionof corrected sensor values for the sensor 128A (see FIG. 3).

When the current mode_(t) is not equal to INITIALIZE, in block 220-B,the monitor 136 corrects the sensor value C′ for drift to obtain thecorrected value C and adds the corrected value C to the collection ofcorrected sensor values for the sensor 128A (see FIG. 3). The correctedvalue C may be calculated as a function of time, temperature, and thesensor value C′.

Next, in block 225-B, the monitor 136 calculates statistics in real timefor the collection of corrected sensor values accumulated for the sensor128A (see FIG. 3). The statistics may include a mean, a standarddeviation, and a linear least squares slope and intercept.

In block 230-B, the monitor 136 determines an integral value for thecollection of corrected sensor values accumulated for the sensor 128A(see FIG. 3). The data may be numerically integrated in real time as thesummation of each trapezoidal area above and/or below a baseline value(e.g., integral value=Σ1/2(C_(t)−C_(t−1))·Δt).

In decision block 235-B, the monitor 136 determines whether the currentmode_(t) is equal to ROUTINE or TRIPPED.

When the current mode_(t) is not equal to either ROUTINE or TRIPPED, themonitor 136 advances to decision block 240-B.

On the other hand, when the current mode_(t) is equal to ROUTINE orTRIPPED, in block 245-B, the monitor 136 sets the Trigger Condition(“TC”) for the sensor 128A (see FIG. 3). The monitor 136 may set the TCto the triggered value (e.g., one) when the corrected value C hasexceeded a threshold value. The threshold value may be a proportionalthreshold, a derivative threshold, or an integral threshold. The monitor136 may set the TC to the not triggered value (e.g., zero) when thecorrected value C has not exceeded the threshold value.

The corrected value C is an instantaneous concentration of a singleanalyte, ΣC is the instantaneous concentration of a group of analytes,and t is time. As mentioned above, C₀ is the baseline of the sensor 128A(see FIG. 3). In block 245-B, the monitor 136 may determine thecorrected value C has exceeded the threshold value when a proportionalmeasurement estimate (C/C₀ or ΣC/C₀), its integral (∫CΔt or ∫ΣCΔt,respectively), or its derivative (ΔC/Δt or ΣΔΣC/Δt, respectively), orany combination thereof (a) falls outside of one of upper and lowerconfidence bounds UB and LB (see FIG. 8B) and lies toward a moredangerous condition, or (b) passes an absolute boundary (e.g., exceeds aparticular threshold value).

At block 245-B, the monitor 136 may determine the upper and lowerconfidence bounds UB and LB (see FIG. 8B) for each of the fire detectionsensor(s) 216 (e.g., the sensor 128A illustrated in FIG. 3). As one ofordinary skill in the art will recognize, there is no mathematicaldistinction between removing sensor drift and accommodating sensor driftand the subsequent examples may use either formulation to mean the samething. To illustrate the foregoing, consider a first sensor that isreading a true concentration value of 300 ppm and a newly calibratedsecond sensor that also reads about 300 ppm. After some time, the secondsensor is reading 310 ppm, while the actual concentration remains at 300ppm. In other words, the output of the second sensor has drifted by +10ppm. The +10 ppm drift can be either be removed or accommodated. Ifremoval is chosen, the reading is adjusted downward by 10 ppm. On theother hand, if accommodation is chosen, the new calibration level issimply set to 310 ppm.

In block 245-B, the System Controller 190 may address drift by applyinga variant of the “Random Walk” model to the sensor's historical data.Using this approach, a difference between any data point and its priorvalue (called the series “first difference”) is calculated, transformed,and modeled to determine the upper and lower confidence bounds UB and LB(see FIG. 8B) for the change in any two sequential measurements.

In addition, the upper and lower confidence bounds UB and LB (see FIG.8B) for cumulative changes of subsequent measurements over time, andabsolute values (actual sensor readings) are also developed (asillustrated in FIG. 8B). The upper and lower confidence bounds UB and LBare based on different confidence levels, and the latter is varieddepending on the reliability of the sensor. The upper and lowerconfidence bounds UB and LB are updated periodically by including newdata.

In decision block 250-B, the monitor 136 determines whether the TC ofthe sensor 128A (see FIG. 3) is set to the not triggered value (e.g.,zero).

When the Trigger Condition is set to other than the not triggered value(e.g., zero), in block 255-B, the monitor 136 sets the trip state (“TS”)of the sensor 128A (see FIG. 3). For example, if the TS of the sensor128A is the not tripped value (e.g., zero), the monitor 136 may increase(or increment) that TS to the single trip value (e.g., one). Similarly,if the TS of the sensor 128A is set to the single trip value (e.g.,one), the monitor 136 may set the TS equal to the consecutively trippedvalue (e.g., two), which is the highest possible TS for a single sensor.The monitor 136 may also set the report time associated with the sensor128A equal to the non-routine value (e.g., 30 seconds).

In decision block 260-B, the monitor 136 determines whether the currentmode_(t) is equal to ROUTINE. When the current mode_(t) is equal toROUTINE, in block 265-B, the monitor 136 sets the current mode_(t) toTRIPPED. On the other hand, when the current mode_(t) is not equal toROUTINE, the monitor 136 advances to decision block 240-B.

In decision block 240-B, the monitor 136 determines whether the reporttime has elapsed. When the report time has not elapsed, the monitor 136advances to block 270-B. On the other hand, when the report time haselapsed, in block 275-B, the monitor 136 uploads the collection ofcorrected sensor values, the collection of sensor values, and the TS forthe sensor 128A (see FIG. 3) to the System Controller 190. Then, themonitor 136 advances to block 270-B.

In block 270-B, the monitor 136 checks (e.g., a download buffer) for newflag values and sensor parameters received from the System Controller190. If new values are available, the monitor 136 stores them in thememory 130M. The monitor 136 may over-write its previous values with thenew values. Then, the monitor 136 returns to block 205-B to continue thepolling loop.

When the monitor 136 determines in decision block 250-B that the TriggerCondition is set to the not triggered value (e.g., zero), the monitor136 advances to decision block 280-B. In decision block 280-B, themonitor 136 determines whether the current mode_(t) is equal to TRIPPED.

When the current mode_(t) is not equal to TRIPPED, the monitor 136advances to decision block 240-B.

When the current mode_(t) is equal to TRIPPED, in block 285-B, themonitor 136 sets the current mode_(t) equal to ROUTINE and sets thereport time equal to the routine value (e.g., 15 minutes) for the sensor128A (see FIG. 3). Then, the monitor 136 advances to decision block240-B.

Thus, the monitor 136 may use the method 200-B to supply, to the SystemController 190, the collection of corrected sensor values, thecollection of sensor values, and the TS for each of the fire detectionsensor(s) 216 (e.g., the sensor 128A illustrated in FIG. 3) at eachexpiration of the report time for the sensor. In other words, themonitor 136 may use the method 200-B to continuously supply informationto the System Controller 190 collected from each of the fire detectionsensor(s) 216 (see FIG. 3).

FIGS. 7C-7E are a flow diagram of the evaluate method 200-C performed bythe System Controller 190.

Referring to FIG. 7C, in first block 205-C, the System Controller 190receives the information uploaded by the monitor 136 in block 275-B (seeFIG. 7B) in method 200-B (see FIG. 7B).

In decision block 210-C, the System Controller 190 determines whetherthe current mode_(t) is equal to INITIALIZE.

When the current mode_(t) is equal to INITIALIZE, the System Controller190 advances to block 215-C. In block 215-C, the System Controller 190records the information uploaded to the System Controller 190 by themonitor 136 in block 275-B (see FIG. 7B) in method 200-B (see FIG. 7B).For example, the System Controller 190 records the current mode_(t), thefan speed, and the report time. Then, in block 273, the SystemController 190 may communicate (e.g., push) to the monitor 136 anyoperational flag changes including the current mode_(t), the previousmode_(t−1), the fan speed, and the report time.

When the current mode_(t) is not equal to INITIALIZE, the SystemController 190 advances to decision block 220-C. In decision block220-C, the System Controller 190 determines whether the current mode_(t)is equal to DRIFT1.

When the current mode_(t) is equal to DRIFT1, the System Controller 190advances to block 225-C. In block 225-C, the System Controller 190performs a dilution one test method 200-R (see FIG. 7R). Then, theSystem Controller 190 advances to the block 215-C.

When the current mode_(t) is not equal to DRIFT1, the System Controller190 advances to decision block 230-C. In decision block 230-C, theSystem Controller 190 determines whether the current mode_(t) is equalto DRIFT2.

When the current mode_(t) is equal to DRIFT2, the System Controller 190advances to block 235-C. In block 235-C, the System Controller 190performs a dilution two test method 200-S (see FIG. 7S). Then, theSystem Controller 190 advances to the block 215-C.

When the current mode_(t) is not equal to DRIFT2, the System Controller190 advances to decision block 240-C. In decision block 240-C, theSystem Controller 190 determines whether the current mode_(t) is equalto TRIPPED. The decision in decision block 240-C is “YES” when thecurrent mode_(t) is equal to TRIPPED. Otherwise, the decision indecision block 240-C is “NO.”

When the decision in decision block 240-C is “YES,” the SystemController 190 advances to block 205-D (see FIG. 7D). Referring to FIG.7D, in block 205-D, the System Controller 190 performs a corroboratemethod 200-I (see FIG. 71). The System Controller 190 calculates aweighted TS sum value when the System Controller 190 performs thecorroborate method 200-I (see FIG. 71). Then, in block 210-D, the SystemController 190 performs a coordinate method 200-J (see FIG. 7J). Theweighted TS sum value may be modified (e.g., increased) when the SystemController 190 performs the coordinate method 200-J (see FIG. 7J). Next,the System Controller 190 advances to decision block 215-D.

In decision block 215-D, the System Controller 190 determines whetherthe weighted TS sum value is greater than or equal to an alarm threshold(“AT”). By way of a non-limiting example, the AT may be 3.5. If theweighted TS sum value is greater than or equal to the AT, validation iswarranted. Otherwise, validation is not warranted. The decision indecision block 215-D is “YES” when the weighted TS sum value is greaterthan or equal to the AT. Otherwise, the decision in decision block 215-Dis “NO.”

When the decision in decision block 215-D is “NO,” in block 220-D, thealarm state value of the AS for the current time (t) is set to the lowvalue (e.g., zero). The event type indicator may also be set to the noevent value (e.g. to zero). Then, in block 225-D, the System Controller190 performs a lowest notification method 200-H (see FIG. 7H). Next, theSystem Controller 190 advances to block 215-C.

When the decision in decision block 215-D is “YES,” in block 230-D theSystem Controller 190 performs a calculate method 200-K (see FIG. 7K).Then, in decision block 235-D, the System Controller 190 determineswhether the alarm state value of the AS for the current time (t) isgreater than the low value (e.g., zero). The decision in decision block235-D is “YES,” when the alarm state value of the AS for the currenttime (t) is greater than the low value. Otherwise, the decision indecision block 235-D is “NO.”

When the decision in decision block 235-D is “NO,” in block 225-D, theSystem Controller 190 performs the lowest notification method 200-H (seeFIG. 7H). Then, the System Controller 190 advances to block 215-C.

When the decision in decision block 235-D is “YES,” in block 240-D, theSystem Controller 190 performs a validate method 200-L (see FIG. 7L).Then, the System Controller 190 advances to decision block 245-D whereatthe System Controller 190 determines whether the current mode_(t) is setto DRIFT1 or DRIFT2. The decision in decision block 245-D is “YES,” whenthe current mode_(t) is set to DRIFT1 or DRIFT2. Otherwise, the decisionin decision block 245-D is “NO.”

When the decision in decision block 245-D is “YES,” the SystemController 190 advances to block 215-C.

When the decision in decision block 245-D is “NO,” the System Controller190 advances to decision block 250-D. In decision block 250-D, theSystem Controller 190 determines whether a validity indicator (obtainedin block 240-D) is greater than a validation threshold. The decision indecision block 250-D is “YES,” when the validity indicator is greaterthan the validation threshold. Otherwise, the decision in decision block250-D is “NO.”

When the decision in decision block 250-D is “NO,” in block 225-D, theSystem Controller 190 performs the lowest notification method 200-H (seeFIG. 7H). Then, the System Controller 190 advances to block 215-C (seeFIG. 7C).

When the decision in decision block 250-D is “YES,” in decision block255-D, the System Controller 190 determines whether the alarm statevalue of the AS for the current time (t) is greater than theintermediate value (e.g., one). The decision in decision block 255-D is“YES,” when the alarm state value of the AS for the current time (t) isgreater than the intermediate value. Otherwise, the decision in decisionblock 255-D is “NO.”

When the decision in decision block 255-D is “YES,” in block 260-D, theSystem Controller 190 performs a highest notification method 200-F (seeFIG. 7F). Then, the System Controller 190 advances to block 215-C (seeFIG. 7C).

When the decision in decision block 255-D is “NO,” in block 265-D, theSystem Controller 190 performs an intermediate notification method 200-G(see FIG. 7G). Then, the System Controller 190 advances to block 215-C(see FIG. 7C).

Referring to FIG. 7C, when the decision in decision block 240-C is “NO,”the System Controller 190 advances to decision block 245-C. In decisionblock 245-C, the System Controller 190 determines whether the currentmode_(t) is equal to CALIBRATE1 or CALIBRATE2.

When the current mode_(t) is equal to CALIBRATE1 or CALIBRATE2, theSystem Controller 190 advances to block 250-C. In block 250-C, theSystem Controller 190 performs a desaturate method 200-0 (see FIG. 7O).Then, the System Controller 190 advances to block 255-C and performs acalibrate method 200-P (see FIG. 7P). Next, the System Controller 190advances to block 260-C and performs a relate method 200-Q (see FIG.7Q). Then, the System Controller 190 advances to block 215-C.

Referring to FIG. 7E, when the current mode_(t) is not equal toCALIBRATE1 or CALIBRATE2, the System Controller 190 advances to decisionblock 210-E. In decision block 210-E, the System Controller 190determines whether the elapsed time exceeds a calibration cadence (“CC”)value (e.g., determined by the relate method 200-Q illustrated in FIG.7Q).

When the elapsed time does not exceed the CC value, the SystemController 190 advances to block 220-E.

When the elapsed time exceeds the CC value, in block 230-E, the SystemController 190 advances to decision block 230-E whereat the SystemController 190 determines whether dilution of the second type isavailable. When dilution of the second type is available, in block240-E, the System Controller 190 sets the current mode_(t) equal toCALIBRATE2. Otherwise, in block 250-E, the System Controller 190 setsthe current mode_(t) equal to CALIBRATE1. Then, the System Controller190 advances to block 220-E.

In block 220-E, the System Controller 190 performs the calculate method200-K (see FIG. 7K).

Then, in decision block 260-E, the System Controller 190 determineswhether the elapsed time exceeds the baseline time for the sensor 128A(see FIG. 3). Referring to FIG. 7C, when the elapsed time exceeds thebaseline time, in block 260-C, the System Controller 190 performs therelate method 200-Q (see FIG. 7Q). Then, the System Controller 190advances to block 215-C.

Referring to FIG. 7C, when the elapsed time does not exceed the baselinetime, the System Controller 190 advances to block 215-C.

FIG. 7F is a flow diagram of the highest notification method 200-F,which the System Controller 190 may perform in block 260-D (see FIG. 7D)of the evaluate method 200-C illustrated in FIGS. 7C-7E. Referring toFIG. 7F, in first decision block 210-F, the System Controller 190determines whether the alarm state value of the AS for the current time(t) is equal to the alarm state value of the AS for the previous time(t−1). When these two alarm state values are equal, the decision indecision block 210-F is “YES.” Otherwise, the decision in decision block210-F is “NO.”

When the decision in decision block 210-F is “YES,” the highestnotification method 200-F terminates.

When the decision in decision block 210-F is “NO,” in decision block220-F, the System Controller 190 determines whether the event typeindicator of the sensor 128A (see FIG. 3) is set to the combustionvalue. The decision in decision block 220-F is “YES” when the event typeindicator of the sensor 128A is set to the combustion value. Otherwise,the decision in decision block 220-F is “NO.”

When the decision in decision block 220-F is “YES,” in block 230-F, theSystem Controller 190 sends a severe fire alarm notification to one ormore users. Then, the highest notification method 200-F terminates.

When the decision in decision block 220-F is “NO,” in block 240-F, theSystem Controller 190 sends a severe gas alarm notification to the oneor more users. Then, the highest notification method 200-F terminates.

FIG. 7G is a flow diagram of the intermediate notification method 200-G,which the System Controller 190 may perform in block 265-D (see FIG. 7D)of the evaluate method 200-C illustrated in FIGS. 7C-7E. Referring toFIG. 7G, in first decision block 210-G, the System Controller 190determines whether the alarm state value of the AS for the current time(t) is equal to the alarm state value of the AS for the previous time(t−1). When these two alarm state values are equal, the decision indecision block 210-G is “YES.” Otherwise, the decision in decision block210-G is “NO.”

When the decision in decision block 210-G is “YES,” the intermediatenotification method 200-G terminates.

When the decision in decision block 210-G is “NO,” in decision block220-G, the System Controller 190 determines whether the event typeindicator of the sensor 128A (see FIG. 3) is set to the combustionvalue. The decision in decision block 220-G is “YES” when the event typeindicator of the sensor 128A is set to the combustion value. Otherwise,the decision in decision block 220-G is “NO.”

When the decision in decision block 220-G is “YES,” in block 230-G, theSystem Controller 190 sends a moderate fire alarm notification to theone or more users. Then, the intermediate notification method 200-Gterminates.

When the decision in decision block 220-G is “NO,” in block 240-G, theSystem Controller 190 sends a moderate gas alarm notification to the oneor more users. Then, the intermediate notification method 200-Gterminates.

FIG. 7H is a flow diagram of the lowest notification method 200-H, whichthe System Controller 190 may perform in block 225-D (see FIG. 7D) ofthe evaluate method 200-C illustrated in FIGS. 7C-7E. Referring to FIG.7H, in first decision block 210-H, the System Controller 190 determineswhether the alarm state value of the AS for the current time (t) isequal to the alarm state value of the AS for the previous time (t−1).When these two alarm state values are equal, the decision in decisionblock 210-H is “YES.” Otherwise, the decision in decision block 210-H is“NO.”

When the decision in decision block 210-H is “YES,” the lowestnotification method 200-H terminates.

When the decision in decision block 210-H is “NO,” in decision block220-H, the System Controller 190 determines whether the event typeindicator of the sensor 128A (see FIG. 3) is set to the combustionvalue. The decision in decision block 220-H is “YES” when the event typeindicator of the sensor 128A is set to the combustion value. Otherwise,the decision in decision block 220-H is “NO.”

When the decision in decision block 220-H is “YES,” in block 230-H, theSystem Controller 190 sends an all clear notification to the one or moreusers. Then, the lowest notification method 200-H terminates.

When the decision in decision block 220-H is “NO,” in block 240-H, theSystem Controller 190 sends a no gas leak notification to the one ormore users. Then, the lowest notification method 200-H terminates.

FIG. 7I is a flow diagram of the corroborate method 200-I, which theSystem Controller 190 may perform in block 205-D (see FIG. 7D) of themethod 200-C (see FIGS. 7C-7E).

In first block 210-I, the System Controller 190 increases the trip state(TS) for the sensor 128A (see FIG. 3). For example, the TS may beincreased by one for each sequential alarm condition. As mentionedabove, the TS is capped at the consecutively tripped value (e.g., two).

Then, in block 220-I, the System Controller 190 determines the weightedTS sum value for the sensor 128A (see FIG. 3). The System Controller 190may calculate the weighted TS sum value by totaling the product of theindividual TS value and its associated weight for each of the firedetection sensor(s) 216 (e.g., weighted TS sum value=Σ(TS(N)·W(N))). Theweight(s) may be determined in block 245-Q (see FIG. 7Q) of the relatemethod 200-Q (see FIG. 7Q).

Then, the corroborate method 200-I terminates.

FIG. 7J is a flow diagram of the coordinate method 200-J, which theSystem Controller 190 may perform in block 210-D (see FIG. 7D) of themethod 200-C (see FIGS. 7C-7E).

In first block 210-J, the System Controller 190 identifies adjacentvaults (e.g., using a user-defined radius and the geo-coordinates of allof the vaults).

Then, in decision block 220-J, the System Controller 190 determineswhether any of the adjacent vaults are in an alarm condition. Thedecision in decision block 220-J is “YES,” when at least some of theadjacent vaults are in an alarm condition. Otherwise, the decision indecision block 220-J is “NO” and the coordinate method 200-J terminates.

When the decision in decision block 220-J is “YES,” in block 230-J, theSystem Controller 190 identifies any redundant or complimentary sensorsin an alarm state that are within the adjacent vaults in an alarmcondition. Such sensors are reading corroborating perturbations.

Then, in block 240-J, the System Controller 190 adds the TS of thesensors identified in block 230-J to the weighted TS sum value of eachof the vaults identified in block 210-J and to the weighted TS sum ofthe vault 112. Then, the coordinate method 200-J terminates.

FIG. 7K is a flow diagram of the calculate method 200-K, which theSystem Controller 190 may perform in blocks 230-D (see FIG. 7D) and220-E (see FIG. 7E) of the evaluate method 200-C (see FIGS. 7C-7E).

The System Controller 190 performs the calculate method 200-K todetermine the event type indicator for the sensor 128A (see FIG. 3) atthe current time (t) and delineate between small and large events. TheSystem Controller 190 may use either a component mass balance or adelineation method and concentration thresholds to estimate eventmagnitude. The concentration thresholds may include the followingvalues:

-   -   1. A burn nuisance threshold (e.g., 0.1 g/s for the component        mass balance and 1000 ppm for the delineation method),    -   2. A burn level delimiter (e.g., 1.0 g/s the component mass        balance and 2000 ppm for the delineation method),    -   3. A FGA nuisance threshold (e.g., 0.1 g/s the component mass        balance and 2000 ppm for the delineation method), and    -   4. A FGA level delimiter (e.g., 1.0 g/s the component mass        balance and 4000 ppm for the delineation method).        The concentration thresholds may be preset default values, user        specified values, or values set by an artificial intelligence        algorithm. The concentration thresholds may be specified for all        of the vaults or different values may be specified for at least        some of the vaults.

In decision block 202-K, the System Controller 190 determines whetherVOCs are present inside the vault 112. For example, the decision indecision block 202-K may be “YES” when the System Controller 190determines VOCs are present, but fire by-products, such as CO, CO₂, NO,NO₂, and O₃, are at non-fire levels. The System Controller 190 maydetermine that VOCs are present when the concentration of VOCs isgreater than 2000 ppm. The System Controller 190 may determine that CO,CO₂, NO, NO₂, and O₃ are at non-fire levels when their concentrationstotal less than 1000 ppm.

When the decision in decision block 202-K is “YES,” in block 204-K, theSystem Controller 190 sets the event type indicator for the current time(t) and the sensor 128A (see FIG. 3) to the FGA value (e.g., two).

Then, in block 206-K, the System Controller 190 determines a flammablegas accumulation (“FGA”). Flammable gas accumulation is a rate at whichthe flammable gas(es) (e.g., VOCs and H₂S) are being introduced into thevault 112. The System Controller 190 may perform either a component massbalance or a delineation method to determine the FGA. The component massbalance, energy balance, and water balance are described below. Thedelineation method may include calculating the FGA using the followingEquation 6:

FGA=C _(CO)+CH₂+C_(VOC)   (6)

Next, in decision block 210-K, the System Controller 190 decides whetherthe FGA is greater than the FGA nuisance threshold. The decision indecision block 210-K is “YES” when the FGA is greater than the FGAnuisance threshold. Otherwise, the decision in decision block 210-K is“NO.”

When the decision in decision block 210-K is “NO,” in block 212-K, theSystem Controller 190 sets the alarm state value to the low value (e.g.,zero). Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 210-K is “YES,” in block 230-K, theSystem Controller 190 decides whether the FGA is greater than the FGAlevel delimiter. The decision in decision block 230-K is “YES” when theFGA is greater than the FGA level delimiter. Otherwise, the decision indecision block 230-K is “NO.”

When the decision in decision block 230-K is “YES,” in block 232-K, theSystem Controller 190 sets the alarm state value equal to the high value(e.g., two). Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 230-K is “NO,” in block 234-K, theSystem Controller 190 sets the alarm state value equal to theintermediate value (e.g., one). Then, the System Controller 190 advancesto block 220-K.

In block 220-K, the System Controller 190 stores the alarm state value,the burn rate, and the FGA.

Then, the calculate method 200-K terminates.

When the decision in decision block 202-K is “NO,” in block 240-K, theSystem Controller 190 sets the event type to the combustion value (e.g.,one).

Then, in block 242-K, the System Controller 190 determines the burnrate. In block 242-K, the System Controller 190 may perform either thecomponent mass balance (described below) or the delineation method todetermine the burn rate. When a component mass balance is used, the burnrate may be expressed as a unit mass consumed per unit time. Thedelineation method may include calculating the burn rate using thefollowing Equation 7:

Burn Rate=C_(CO)+C_(CO) ₂ +C_(NO)+C_(NO) ₂ +C_(O) ₃ +max(0,1000*(20.95%−C_(O) ₂ %))   (7)

When Equation 7 is used, the burn rate may be expressed in ppm.

Next, in decision block 250-K, the System Controller 190 decides whetherthe burn rate is greater than the burn nuisance threshold. The decisionin decision block 250-K is “YES” when the burn rate is greater than theburn nuisance threshold. Otherwise, the decision in decision block 250-Kis “NO.”

When the decision in decision block 250-K is “NO,” in block 254-K, theSystem Controller 190 sets the alarm state value for the current time(t) and the sensor 128A (see FIG. 3) to the low value (e.g., zero).Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 250-K is “YES,” in decision block256-K, the System Controller 190 decides whether the burn rate isgreater than the burn level delimiter. The decision in decision block256-K is “YES” when the burn rate is greater than the burn leveldelimiter. Otherwise, the decision in decision block 256-K is “NO.”

When the decision in decision block 256-K is “NO,” in block 260-K, theSystem Controller 190 sets the alarm state value for the current time(t) and the sensor 128A (see FIG. 3) to the intermediate value (e.g.,one). Then, the System Controller 190 advances to block 220-K.

When the decision in decision block 256-K is “YES,” in block 262-K, theSystem Controller 190 sets the alarm state value for the current time(t) and the sensor 128A (see FIG. 3) to the high value (e.g., two).Then, the System Controller 190 advances to block 220-K.

Then, the calculate method 200-K terminates.

FIG. 7L is a flow diagram of the validate method 200-L, which the SystemController 190 may perform in block 240-D (see FIG. 7D) of the evaluatemethod 200-C (see FIGS. 7C-7E). The validate method 200-L may includetwo parallel validation processes, labeled “DRIFT” and “PERSISTENCE” inFIG. 7L. The first (“DRIFT”) validation process confirms that drift hasnot caused those sensor readings in alarm condition to be in thatcondition. The second (“PERSISTENCE”) validation process confirms thatthe alarm condition meets user-defined persistence. As a non-limitingexample of persistence, imagine that a truck stops directly over thefresh air inlet of a manhole cover and spews combustion products intothe manhole. If that situation persists for only the length of time of asingle stop light cycle, an alarm would be a false positive alarm.

In block 210-L, the System Controller 190 performs a drift validationprocess 200-M (see FIG. 7M) and obtains a validity value (“W”).

In block 220-L, the System Controller 190 performs a persistencevalidation process 200-N (see FIG. 7N) and obtains a persistence value.

In block 230-L, the System Controller 190 totals the persistence valueand the VV to obtain a validity indicator. Then, the validate method200-L terminates.

FIG. 7M is a flow diagram of the drift validation process 200-M, whichthe System Controller 190 may perform in block 210-L (see FIG. 7L) ofthe validate method 200-L (see FIG. 7L).

In first block 205-M, the System Controller 190 initializes the VV. Forexample, in block 205-M, the System Controller 190 may set the VV equalto zero.

In decision block 210-M, the System Controller 190 determines whetherdilution of the second type is available. The decision in decision block210-M is “YES” when dilution of the second type is available. Otherwise,the decision in decision block 210-M is “NO.”

When the decision in decision block 210-M is “YES,” in block 215-M, theSystem Controller 190 performs the dilution two test method 200-S (seeFIG. 7S) and obtains the drift test result. Then, the System Controller190 advances to decision block 220-M.

When the decision in decision block 210-M is “NO,” in decision block225-M, the System Controller 190 determines whether dilution of thefirst type is available. The decision in decision block 225-M is “YES”when dilution of the first type is available. Otherwise, the decision indecision block 225-M is “NO.”

When the decision in decision block 225-M is “NO,” the drift validationprocess 200-M terminates.

When the decision in decision block 225-M is “YES,” in block 230-M, theSystem Controller 190 performs the dilution one test method 200-R (seeFIG. 7R) and obtains the drift test result. Then, the System Controller190 advances to decision block 220-M.

In decision block 220-M, the System Controller 190 determines whetherthe TS of the sensor 128A (see FIG. 3) is set to the consecutivelytripped value (e.g., two). The decision in decision block 220-M is “YES”when the TS of the sensor 128A is set to the consecutively trippedvalue. Otherwise, the decision in decision block 220-M is “NO.”

When the decision in decision block 220-M is “NO,” the drift validationprocess 200-M terminates.

When the decision in decision block 220-M is “YES,” in decision block235-M, the System Controller 190 determines whether the drift testresult indicates that the sensor 128A (see FIG. 3) has passed. Thedecision in decision block 235-M is “YES” when the drift test resultindicates that the sensor 128A has passed. Otherwise, the decision indecision block 235-M is “NO.”

When the decision in decision block 235-M is “YES,” in block 240-M, theSystem Controller 190 updates the VV. For example, the System Controller190 may add one to the VV. By way of another non-limiting example, thedrift test result may be a first value (e.g., one) when the sensor 128A(see FIG. 3) passed and a different second value (e.g., zero) when thesensor 128A failed. In such embodiments, the drift test result may beadded to the VV. Then, the System Controller 190 returns to decisionblock 220-M.

When the decision in decision block 235-M is “NO,” in decision block245-M the System Controller 190 determines whether dilution of thesecond type is available. The decision in decision block 245-M is “YES”when dilution of the second type is available. Otherwise, the decisionin decision block 245-M is “NO.”

When the decision in decision block 245-M is “NO,” the System Controller190 returns to decision block 220-M.

When the decision in decision block 245-M is “YES,” in decision block250-M, the System Controller 190 determines whether the sensor 128A (seeFIG. 3) should be calibrated. By way of a non-limiting example, theSystem Controller 190 may determine it is time to calibrate the sensor128A when at least a predetermined portion (e.g., 10%) of thecalibration cadence (“CC”) time has transpired since the previouscalibration of the sensor 128A (see FIG. 3). The predetermined portionmay be specified by a user.

When the decision in decision block 250-M is “NO,” the System Controller190 returns to decision block 220-M.

When the decision in decision block 250-M is “YES,” in block 255-M, theSystem Controller 190 performs the calibrate method 200-P (see FIG. 7P).Then, the System Controller 190 returns to decision block 220-M.

FIG. 7N is a flow diagram of the persistence validation process 200-N,which the System Controller 190 may perform in block 220-L (see FIG. 7L)of the validate method 200-L (see FIG. 7L).

In first block 210-N, the System Controller 190 determines the eventtime for the sensor 128A (see FIG. 3). By way of a non-limiting example,the event time may be the sample time minus the event start time. Theevent start time is the time when the first sensor tripped (e.g., whenany TS(N)>0).

Then, in decision block 220-N, the System Controller 190 determineswhether the alarm state value at the current time is greater than theintermediate value (e.g., one), meaning the event is large. The decisionin decision block 220-N is “YES” when the event is large. Otherwise, thedecision in decision block 220-N is “NO.”

When the decision in decision block 220-N is “YES,” in block 230-N, theSystem Controller 190 sets the persistence value equal to the event time(determined in block 210-N) divided by a large persistence divisor. Thelarge persistence divisor may be user defined or calculated by theSystem Controller 190. The greater the persistence divisor, the greaterpersistence is required to trigger an alarm state. For example, if theevent is large, the large persistence divisor is equal to 60 seconds,and the event time is 30 seconds, the persistence value would equal 0.5(30/60=0.5). Then, the persistence validation process 200-N terminates.

When the decision in decision block 220-N is “NO,” the event is small.In block 240-N, the System Controller 190 sets the persistence valueequal to the event time (determined in block 210-N) divided by a smallpersistence divisor. The small persistence divisor may be user definedor calculated by the System Controller 190. For example, when the eventis small, the small persistence divisor is equal to 300 seconds, and theevent time is 30 seconds, the persistence value would equal 0.1(30/300=0.1). Then, the persistence validation process 200-N terminates.

FIG. 7O is a flow diagram of the desaturate method 200-O, which theSystem Controller 190 may perform in block 250-C (see FIG. 7C) of theevaluate method 200-C (see FIGS. 7C-7E). For sensors that are at or neartheir saturation limits, the System Controller 190 may perform thedesaturate method 200-0, which allows perturbations in dilution to bringthe sensor back into its operational range.

In first block 210-O, the System Controller 190 may record thestatistics determined in blocks 225-B and 230-B (see FIG. 7B) of themethod 200-B (see FIG. 7B).

In decision block 220-O, the System Controller 190 determines whetherdilution of the second type is available. The decision in decision block220-O is “YES” when dilution of the second type is available. Otherwise,the decision in decision block 220-O is “NO.”

When the decision in decision block 220-O is “YES,” in block 230-O, theSystem Controller 190 performs a dilution two range method 200-W (seeFIG. 7W). Then, the desaturate method 200-O terminates.

When the decision in decision block 220-O is “NO,” in decision block240-O, the System Controller 190 determines whether dilution of thefirst type is available. The decision in decision block 240-O is “YES”when dilution of the first type is available. Otherwise, the decision indecision block 240-O is “NO.”

When the decision in decision block 240-O is “NO,” the desaturate method200-O terminates.

When the decision in decision block 240-O is “YES,” in block 250-O, theSystem Controller 190 performs a dilution one range method 200-V (seeFIG. 7V). Then, the desaturate method 200-O terminates.

FIG. 7P is a flow diagram of the calibrate method 200-P, which theSystem Controller 190 may perform in block 255-C of the evaluate method200-C (see FIGS. 7C-7E) and in block 255-M of the drift validationprocess 200-M (see FIG. 7M). The System Controller 190 may use thecalibrate method 200-P to calibrate the fire detection sensor(s) 216(e.g., the sensor 128A illustrated in FIG. 3). The fire detectionsensor(s) 216 (see FIG. 3) may be recalibrated routinely when thecalibration cadence time is exceeded (and the current mode_(t) is set toCALIBRATE2 in block 240-E or CALIBRATE1 in block 250-E of FIG. 7E) or ondemand to confirm accurate values when an event is detected or anunusual circumstance suggests an additional calibration may be prudent.

In first block 210-P, the System Controller 190 may record thestatistics determined in blocks 225-B and 230-B (see FIG. 7B) of themethod 200-B (see FIG. 7B).

In decision block 220-P, the System Controller 190 determines whetherdilution of the second type is available. The decision in decision block220-P is “YES” when dilution of the second type is available. Otherwise,the decision in decision block 220-P is “NO.”

When the decision in decision block 220-P is “YES,” in block 230-P, theSystem Controller 190 performs a dilution two calibration method 200-U(see FIG. 7U). Then, the calibrate method 200-P terminates.

When the decision in decision block 220-P is “NO,” in decision block240-P, the System Controller 190 determines whether dilution of thefirst type is available. The decision in decision block 240-P is “YES”when dilution of the first type is available. Otherwise, the decision indecision block 240-P is “NO.”

When the decision in decision block 240-P is “NO,” the calibrate method200-P terminates.

When the decision in decision block 240-P is “YES,” in block 250-P, theSystem Controller 190 performs a dilution one calibration method 200-T(see FIG. 7T). Then, the calibrate method 200-P terminates.

FIG. 7Q is a flow diagram of the relate method 200-Q, which the SystemController 190 may perform in block 260-C (see FIG. 7C) of the evaluatemethod 200-C (see FIGS. 7C-7E). The System Controller 190 performs therelate method 200-Q to find statistical relationships between eachsensor's values (C(N)) and both time and temperature (t and T,respectively). Relationships may be determined for proportional,derivative, and/or integral trends.

In first block 205-Q, the System Controller 190 reads sensor values overstatistically relevant historical periods (e.g., the baseline time orgreater). In block 205-Q, the System Controller 190 may ignore dataassociated with alarm state values other than the low value (e.g., zero)and/or data associated with a current mode_(t) other than ROUTINE.

In block 210-Q, the System Controller 190 fits the relevant sensor datato a model. For example, the System Controller 190 may fit the relevantsensor data to a linear equation, such as Equation 8 below:

Y=mt+m′T+b   (8)

In Equation 8, a variable m is time-based DRIFT slope, a variable m′ isa temperature-based slope, a variable b is the Y-axis intercept, and avariable Y is the difference between a sensor reading and its assumed(calibrated or imputed) value. While Equation 8 may be used to model thedata, other equations may also be used. For example, if a linearfunction of C to time (t) or temperature (T) does not adequately fit thedata, additional terms, different equation forms, or variabletransformations may be used to reflect such non-linearities.

In block 215-Q, the System Controller 190 determines a thresholdconcentration limit (e.g., using a user or AI chosen confidence level)for each sensor.

In block 220-Q, the System Controller 190 determines a thresholdconcentration derivative limit (e.g., using a user or AI chosenconfidence level) for each sensor. The derivative (or slope) is withrespect to concentration over time.

In block 225-Q, the System Controller 190 determines a thresholdconcentration integral limit (e.g., using a user or AI chosen confidencelevel) for each sensor.

In block 230-Q, the System Controller 190 identifies a time of day(e.g., in the diurnal cycle) when the temperature is likely to belowest. In block 235-Q, the System Controller 190 determines acalibration cadence (“CC”) value. By way of a non-limiting example, thecalibration cadence value may be set to 24 hours. Calibration is bestdone at the lowest temperature, which is determined in block 230-Q. Thecoolest part of the day in the manhole may depend greatly on the localweather because the temperature of the vault 112 is driven by outsideair temperature and load on cables and equipment. Historical values,weather forecasts, and/or load forecasts can be referenced to choose thebest time. The slope of the drift is another factor in setting thecalibration cadence value. If the drift is not material, the calibrationcadence value can be lengthened. On the other hand, if drift is amaterial issue, the calibration cadence value can be shortened.Calibration with dilution of the second type essentially takes thesensors off-line during a short calibration period. Therefore,maximizing the calibration cadence value provides the most robustmonitoring when calibration with dilution of the second type is used.

In block 240-Q, the System Controller 190 determines a baseline cadence(“BLC”) value. By way of a non-limiting example, the BLC value may beset to 24 hours. The BLC value is a length of time that elapses betweenthe recalculation of the sensor baseline and threshold values. If theslope of the drift and the noisiness of the data are consistent acrosstwo baselines, the BLC value may be increased. The converse suggests ashortening of the BLC value.

In block 245-Q, the System Controller 190 determines a weight for eachof the fire detection sensor(s) 216 (e.g., the sensor 128A illustratedin FIG. 3). For example, each of the fire detection sensor(s) 216 (seeFIG. 3) may be assigned a weight between zero and one. A weight of zerocauses that sensor to be ignored. A weight of zero may be appropriatefor a sensor that has failed. A weight of one indicates that the sensoris working as designed and is believed to be providing reliable data.The System Controller 190 may use one or more of the followingconsiderations when assigning a weight to each of the fire detectionsensor(s) 216 (see FIG. 3):

-   -   1. Sensor signal to noise        -   a. time-based        -   b. temperature-based    -   2. Sensor drift        -   a. absolute drift        -   b. drift stability (second derivative)    -   3. Sensor within design range    -   4. Time since calibration    -   5. Complementary/redundant sensors corroboration        -   a. Co-located        -   b. Adjacent vaults

In block 250-Q, the System Controller 190 records at least some of thevalues obtained during the performance of the relate method 200-Q (e.g.,baseline values and trigger parameters). The System Controller 190 maydownload at least some of the values obtained during the performance ofthe relate method 200-Q to the monitor 126. Then, the relate method200-Q terminates.

FIG. 7R is a flow diagram of the dilution one test method 200-R, whichthe System Controller 190 may perform in block 225-C (see FIG. 7C) ofthe evaluate method 200-C (see FIGS. 7C-7E) and in block 230-M (see FIG.7M) of the drift validation process 200-M (see FIG. 7M). When performingthe dilution one test method 200-R, the System Controller 190 adjuststhe speed of the air moving device 132 to test if concentrations areperturbed. No perturbation means drift is implicated. On the other hand,perturbations mean measurement is real.

In first decision block 204-R, the System Controller 190 determineswhether the previous mode_(t−1) is set to DRIFT1. When the previous modeis set to DRIFT1, in block 206-R, the System Controller 190 increments adrift1 iteration counter (e.g., adds one to the drift1 iterationcounter). Then, the System Controller 190 advances to decision block210-R.

When the previous mode is not set to DRIFT1, in block 208-R, the SystemController 190 initializes the drift1 iteration counter to aninitialization value (e.g., zero). Then, the System Controller 190advances to decision block 210-R.

In decision block 210-R, the System Controller 190 determines if thedrift1 iteration counter is equal to the initialization value. Thedecision in decision block 210-R is “YES” when the drift1 iterationcounter equals the initialization value. Otherwise, the decision indecision block 210-R is “NO.”

When the decision in decision block 210-R is “YES,” in block 220-R, theSystem Controller 190 saves the previous fan speed then reduces fanspeed by half. The System Controller 190 also sets the current mode_(t)equal to DRIFT1. The fan speed may refer to the speed of the air movingdevice 132. Then, the System Controller 190 advances to decision block230-R.

When the decision in decision block 210-R is “NO,” in block 240-R, theSystem Controller 190 performs tests to identify perturbations. TheSystem Controller 190 may perform one or more of following tests untilstatistically convincing perturbations are recognized within Mτ(tau=time constant for dilution of the first type). By way of anon-limiting example, the value of M may be set initially to two and thevalue of T may be set initially to 300 seconds.

-   -   1. CH₂ should increase from V toward 2V-C_(fresh);    -   2. C_(CO) ₂ should increase from W toward 2W-C_(fresh);    -   3. C_(CO) should increase from X toward 2X-C_(fresh);    -   4. C_(VOC) should increase from Y toward 2Y-C_(fresh);    -   5. C_(O) ₂ should decrease from Z toward 2Z-C_(fresh);    -   6. dC/dt should be positive for CO₂, CO, and VOC; and    -   7. dC/dt should be negative for O₂.        In the above tests, C_(fresh) is the concentration of the        component in fresh air. For example, the value of C_(fresh) may        be 400 ppm for CO₂, 10 ppm for CO, 0 ppm for VOC, and 21.2% for        O₂. When block 240-R is complete, the System Controller 190        advances to decision block 230-R.

In decision block 230-R, the System Controller 190 determines whetherthe test is complete. The drift test is continued until perturbation isconfirmed or not. The decision in decision block 230-R is “YES” when thetest is complete. Otherwise, the decision in decision block 230-R is“NO.”

When the decision in decision block 230-R is “NO,” the current mode_(t)remains set at DRIFT1 and the dilution one test method 200-R terminates.

When the decision in decision block 230-R is “YES,” in block 250-R, theSystem Controller 190 returns the fan speed to the previous value andsets the current mode_(t) equal to ROUTINE. Then, the dilution one testmethod 200-R terminates.

FIG. 7S is a flow diagram of the dilution two test method 200-S, whichthe System Controller 190 may perform in block 235-C (see FIG. 7C) ofthe evaluate method 200-C (see FIGS. 7C-7E) and block 215-M (see FIG.7M) of the drift validation process 200-M (see FIG. 7M). When performingthe dilution two test method 200-S, the System Controller 190 adjuststhe PID control settings of one or both the air moving devices 178 and179 (see FIG. 3) to adjust the IMR and test if concentrations areperturbed. No perturbation means drift is implicated. On the other hand,perturbations mean measurement changes are confirmed.

In first decision block 204-S, the System Controller 190 determineswhether the previous mode_(t−1) is set to DRIFT2. When the previous modeis set to DRIFT2, in block 206-S, the System Controller 190 increments adrift2 iteration counter (e.g., adds one to the drift2 iterationcounter). Then, the System Controller 190 advances to decision block210-S.

When the previous mode is not set to DRIFT2, in block 208-S, the SystemController 190 initializes the drift2 iteration counter to aninitialization value (e.g., zero). Then, the System Controller 190advances to decision block 210-S.

In decision block 210-S, the System Controller 190 determines if thedrift2 iteration counter is equal to the initialization value. Thedecision in decision block 210-S is “YES” when the drift 2 iterationcounter is equal to the initialization value. Otherwise, the decision indecision block 210-S is “NO.”

When the decision in decision block 210-S is “YES,” in block 220-S, theSystem Controller 190 saves the previous IMR and increases the IMR. TheSystem Controller 190 also sets the current mode_(t) equal to DRIFT2.The IMR is a mass ratio of vault exhaust air to fresh air and may rangefrom zero to infinity. By way of a non-limiting example, the SystemController 190 may double the IMR. The IMR may be adjusted by adjustingthe set point of one or both of the PID controllers and air movingdevices 178 and 179. Then, the System Controller 190 advances todecision block 230-S.

When the decision in decision block 210-S is “NO,” in block 240-S, theSystem Controller 190 performs tests to identify perturbations. TheSystem Controller 190 may perform one or more of the following testsuntil statistically convincing perturbations are recognized within Mτ(tau=time constant for dilution of the second type). By way of anon-limiting example, the value of M may be set initially to two and thevalue of T may be set initially to 30 seconds.

-   -   1. C_(H) ₂ should decrease from V toward (V+C_(fresh))/2;    -   2. C_(co) ₂ should decrease from W toward (W+C_(fresh))/2;    -   3. C_(CO) should decrease from X toward (X+C_(fresh))/2;    -   4. C_(VOC) should decrease from Y toward (Y+C_(fresh))/2;    -   5. C_(O) ₂ should increase from Z toward (Z+C_(fresh))/2;    -   6. dC/dt should be negative for CO₂, CO, H₂, and VOC; and    -   7. dC/dt should be positive for O₂.        In the above tests, C_(fresh) is the concentration of the        component in fresh air. For example, the value of C_(fresh) is        may be 400 ppm for CO₂, 10 ppm for CO, 0.5 ppm for H₂, 0 ppm for        VOC, and 21.2% for O₂. When block 240-S is complete, the System        Controller 190 advances to decision block 230-S.

In decision block 230-S, the System Controller 190 determines whetherthe test is complete. The drift test is continued until perturbation isconfirmed or not. The decision in decision block 230-S is “YES” when thetest is complete. Otherwise, the decision in decision block 230-S is“NO.”

When the decision in decision block 230-S is “NO,” the current mode_(t)remains set to DRIFT2 and the dilution two test method 200-S terminates.

When the decision in decision block 230-S is “YES,” in block 250-S, theSystem Controller 190 returns the IMR to the previous value and sets thecurrent mode_(t) equal to ROUTINE. Then, the dilution two test method200-S terminates.

FIG. 7T is a flow diagram of the dilution one calibration method 200-T,which the System Controller 190 may perform in block 250-P (see FIG. 7P)of the calibrate method 200-P (see FIG. 7P).

In first decision block 204-T, the System Controller 190 determineswhether the previous mode_(t−1) is set to CALIBRATE1. When the previousmode_(t−1) is set to CALIBRATE1, in block 206-T, the System Controller190 increments a calibration1 iteration counter (e.g., adds one to thecalibration1 iteration counter). Then, the System Controller 190advances to decision block 210-T.

When the previous mode_(t−1) is not set to CALIBRATE1, in block 208-T,the System Controller 190 initializes the calibration1 iteration counterto an initialization value (e.g., zero). Then, the System Controller 190advances to decision block 210-T.

In decision block 210-T, the System Controller 190 determines whetherthe calibration1 iteration counter is equal to the initialization value.The decision in decision block 210-T is “YES” when the calibration1iteration counter is equal to the initialization value. Otherwise, thedecision in decision block 210-T is “NO.”

When the decision in decision block 210-T is “YES,” in block 220-T, theSystem Controller 190 saves the fan speed of the air moving device 132then sets the fan speed of the air moving device 132 to full (or 100%)or its maximum setting. Then, the System Controller 190 advances toblock 230-T.

When the decision in decision block 210-T is “NO,” the System Controller190 advances to block 230-T.

In block 230-T, the System Controller 190 performs an assumed fresh aircalibration. In block 230-T, the System Controller 190 calibrates thefire detection sensor(s) 216 (see FIG. 3) to fresh air conditions.

In decision block 240-T, the System Controller 190 determines whetherthe assumed fresh air calibration is complete. The decision in decisionblock 240-T is “YES” when the assumed fresh air calibration is complete.Otherwise, the decision in decision block 240-T is “NO.”

When the decision in decision block 240-T is “NO,” the current mode_(t)remains set to CALIBRATE1 and the dilution one calibration method 200-Tterminates.

When the decision in decision block 240-T is “YES,” in block 250-T, theSystem Controller 190 sets the fan speed equal to its previous value andsets the current mode_(t) equal to ROUTINE. Then, the dilution onecalibration method 200-T terminates.

FIG. 7U is a flow diagram of the dilution two calibration method 200-U,which the System Controller 190 may perform in block 230-P (see FIG. 7P)of the calibrate method 200-P (see FIG. 7P). When performing thedilution two calibration method 200-U, the System Controller 190 uses100% fresh air to calibrate the fire detection sensor(s) 216 (e.g., thesensor 128A illustrated in FIG. 3).

In first decision block 204-U, the System Controller 190 determineswhether the previous mode_(t−1) is set to CALIBRATE2. When the previousmode_(t−1) is set to CALIBRATE2, in block 206-U, the System Controller190 increments a calibration2 iteration counter (e.g., adds one to thecalibration2 iteration counter). Then, the System Controller 190advances to decision block 210-U.

When the previous mode_(t−1) is not set to CALIBRATE2, in block 208-U,the System Controller 190 initializes the calibration2 iteration counterto an initialization value (e.g., zero). Then, the System Controller 190advances to decision block 210-U.

In decision block 210-U, the System Controller 190 determines whetherthe calibration2 iteration counter is equal to the initialization value.The decision in decision block 210-U is “YES” when the calibration2iteration counter is equal to the initialization value. Otherwise, thedecision in decision block 210-U is “NO.”

When the decision in decision block 210-U is “YES,” in block 220-U, theSystem Controller 190 saves the IMR then reduces the IMR to zero. TheIMR may be reduced by adjusting the PID control setting of one or bothof the air moving devices 178 and 179. Then, the System Controller 190advances to block 230-U.

When the decision in decision block 210-U is “NO,” the System Controller190 advances to block 230-U.

In block 230-U, the System Controller 190 performs a fresh aircalibration using atmospheric values for the component gases.

In decision block 240-U, the System Controller 190 determines whetherthe fresh air calibration is complete. The decision in decision block240-U is “YES” when the fresh air calibration is complete. Otherwise,the decision in decision block 240-U is “NO.”

When the decision in decision block 240-U is “NO,” the current mode_(t)remains set to CALIBRATE2 and the dilution two calibration method 200-Uterminates.

When the decision in decision block 240-U is “YES,” in block 250-U, theSystem Controller 190 sets the IMR equal to the previous IMR value andsets the current mode_(t) equal to ROUTINE. Then, the dilution twocalibration method 200-U terminates.

FIG. 7V is a flow diagram of the dilution one range method 200-V, whichthe System Controller 190 may perform in block 250-O (see FIG. 70) ofthe desaturate method 200-O (see FIG. 70). When performing the dilutionone range method 200-V, the System Controller 190 adjusts the fan speedto compensate for sensors out of range. The fan speed may refer to thespeed of the air moving device 132.

In first block 205-V, the System Controller 190 obtains a design rangefor each of the fire detection sensor(s) 216 (e.g., the sensor 128Aillustrated in FIG. 3). Thus, in block 205-V, the System Controller 190obtains an upper sensor range and a lower sensor range for each of thefire detection sensor(s) 216 (see FIG. 3).

In next block 210-V, the System Controller 190 obtains the sensor valuescollected over the baseline time for each of the fire detectionsensor(s) 216 (see FIG. 3).

In block 215-V, the System Controller 190 calculates statistics for thesensor values obtained in block 210-V. The statistics may include themean, standard deviation, a maximum value, and a minimum value.

In block 220-V, the System Controller 190 calculates a first probabilityfor each of the fire detection sensor(s) 216 (e.g., the sensor 128Aillustrated in FIG. 3) that the sensor values collected over thebaseline time are greater than the upper sensor range for the sensor.

In block 225-V, the System Controller 190 calculates a secondprobability for each of the fire detection sensor(s) 216 (see FIG. 3)that the sensor values collected over the baseline time are less thanthe lower sensor range for the sensor.

In decision block 230-V, the System Controller 190 determines whetherthe first probability is greater than a first probability threshold. Thedecision in decision block 230-V is “YES” when the first probability isgreater than the first probability threshold. Otherwise, the decision indecision block 230-V is “NO.”

When the decision in decision block 230-V is “YES,” in block 235-V, theSystem Controller 190 calculates an increase in dilution required totarget the sensor readings within the sensor range. For example, inblock 235-V, the System Controller 190 may calculate an increase in thefan speed. By way of a non-limiting example, if the sensor 128A (seeFIG. 3) is near its upper limit, the System Controller 190 may calculatean increase in the fan speed that will keep the sensor 128A within itssensor range. The fan speed may refer to the speed of the air movingdevice 132. Then, the System Controller 190 advances to block 240-V.

When the decision in decision block 230-V is “NO,” the System Controller190 advances to decision block 245-V. In decision block 245-V, theSystem Controller 190 determines whether the second probability isgreater than a second probability threshold. The decision in decisionblock 245-V is “YES” when the second probability is greater than thesecond probability threshold. Otherwise, the decision in decision block245-V is “NO.”

When the decision in decision block 245-V is “YES,” in block 250-V, theSystem Controller 190 calculates a decrease in dilution required totarget the sensor readings within the sensor range. For example, inblock 250-V, the System Controller 190 may calculate a decrease in thefan speed required to move the sensor readings within the sensor range.The fan speed may refer to the fan speed of the air moving device 132.By way of a non-limiting example, if the CO sensor is always readingzero, the System Controller 190 may calculate a decrease in the fanspeed that explores whether CO is present below diluted sensitively.Then, the System Controller 190 advances to block 240-V.

When the decision in decision block 245-V is “NO,” the dilution onerange method 200-V terminates.

In block 240-V, the System Controller 190 adjusts the dilution (e.g.,adjusts the fan speed of the air moving device 132). Then, the dilutionone range method 200-V terminates.

It is possible that a condition could exist where one of the firedetection sensor(s) 216 (see FIG. 3) needs a lower fan speed and anotherone of the fire detection sensor(s) 216 needs a higher fan speed. Whenthis occurs, the dilution one range method 200-V may sequentiallyincrease and decrease the fan speed to accommodate the needs of bothsensors or attempt to strike a balance. Additionally, some of the firedetection sensor(s) 216 are more important than others, which may bepartially reflected in their weights W(N). The weights may be determinedin block 245-Q (see FIG. 7Q) of the relate method 200-Q (see FIG. 7Q).

FIG. 7W is a flow diagram of the dilution two range method 200-W, whichthe System Controller 190 may perform in block 230-O (see FIG. 70) ofthe desaturate method 200-O (see FIG. 70). When performing the dilutiontwo range method 200-W, the System Controller 190 adjusts the IMR tocompensate for sensors out of range. The IMR may be adjusted byadjusting the set points of the PID controllers of one or both of theair moving devices 178 and 179.

In first block 205-W, the System Controller 190 obtains the design rangefor each of the fire detection sensor(s) 216 (e.g., the sensor 128Aillustrated in FIG. 3). Thus, in block 205-W, the System Controller 190obtains the upper sensor range and the lower sensor range for each ofthe fire detection sensor(s) 216 (see FIG. 3).

In block 210-W, the System Controller 190 obtains the sensor valuescollected over the baseline time for each of the fire detectionsensor(s) 216 (see FIG. 3).

In block 215-W, the System Controller 190 calculates statistics for thesensor values obtained in block 210-W. The statistics may include themean, standard deviation, a maximum value, and a minimum value.

In block 220-W, the System Controller 190 calculates a third probabilityfor each of the fire detection sensor(s) 216 (see FIG. 3) that thesensor values collected over the baseline time are greater than theupper sensor range for the sensor.

In block 225-W, the System Controller 190 calculates a fourthprobability for each of the fire detection sensor(s) 216 (see FIG. 3)that the sensor values collected over the baseline time are less thanthe lower sensor range for the sensor.

In decision block 230-W, the System Controller 190 determines whetherthe third probability is greater than a third probability threshold. Thedecision in decision block 230-W is “YES” when the third probability isgreater than the third probability threshold. Otherwise, the decision indecision block 230-W is “NO.”

When the decision in decision block 230-W is “YES,” in block 235-W, theSystem Controller 190 calculates an increase in dilution required totarget the sensor readings within the sensor range. For example, inblock 235-V, the System Controller 190 may calculate an increase in theIMR. The IMR may be adjusted by varying the PID set points on one orboth of the air moving devices 178 and 179. By way of a non-limitingexample, if the sensor 128A (see FIG. 3) is near its upper limit, theSystem Controller 190 may calculate an increase IMR that will keep thesensor 128A within its sensor range. Then, the System Controller 190advances to block 240-W.

When the decision in decision block 230-W is “NO,” the System Controller190 advances to decision block 245-W. In decision block 245-W, theSystem Controller 190 determines whether the fourth probability isgreater than a fourth probability threshold. The decision in decisionblock 245-W is “YES” when the fourth probability is greater than thefourth probability threshold. Otherwise, the decision in decision block245-W is “NO.”

When the decision in decision block 245-W is “YES,” in block 250-W, theSystem Controller 190 calculates a decrease in dilution required toremain the sensor readings within the sensor range. For example, inblock 250-W, the System Controller 190 may calculate a decrease in theIMR required to target the sensor readings within the sensor range. TheIMR is adjusted by varying the set points of the PID controllers of oneor both of the air moving devices 178 and 179. By way of a non-limitingexample, if the CO sensor is always reading zero, the System Controller190 may calculate a decrease in the IMR that explores whether CO ispresent below diluted sensitively. Then, the System Controller 190advances to block 240-W.

When the decision in decision block 245-W is “NO,” the dilution tworange method 200-W terminates.

In block 240-W, the System Controller 190 adjusts the dilution (e.g.,adjusts the IMR). The IMR may be adjusted by adjusting the PIDcontroller set points of one or both of the air moving devices 178 and179. Then, the dilution two range method 200-W terminates.

It is possible that a condition could exist where one of the firedetection sensor(s) 216 (see FIG. 3) needs a lower IMR and another oneof the fire detection sensor(s) 216 needs a higher IMR. When thisoccurs, the dilution two range method 200-W may sequentially increaseand decrease the IMR to accommodate the needs of both sensors or attemptto strike a balance. Additionally, some of the fire detection sensor(s)216 (see FIG. 3) are more important than others, which may be partiallyreflected in their weights W(N). The weights may be determined in block245-Q (see FIG. 7Q) of the relate method 200-Q (see FIG. 7Q).

FIGS. 8A and 8B illustrate the exemplary sensor readings (identified bythe squares 206) obtained from one of the fire detection sensor(s) 216(e.g., the sensor 128A illustrated in FIG. 3). In the example presentedin FIGS. 8A and 8B, the sensor is a carbon dioxide concentration sensorconfigured to measure part-per-million (“ppm”) of carbon dioxide in theinternal atmosphere 124 (see FIG. 1). In both FIGS. 8A and 8B, thex-axis is time and the y-axis is ppm of carbon dioxide.

FIG. 8A illustrates sensor readings received from the carbon dioxideconcentration sensor over a 63-day period from May 10, 2018, to aboutJul. 12, 2018. In this example, the underground vault 112 is located inthe northeast coast of North America. A triple line NNN shows theapproximate sensor drift over the 63-day period starts around 700 ppm onMay 10 and ends at about 1,400 ppm on July. 9. Large positive variations(e.g., readings V1 and V2) indicate burning events within or adjacent tothe manhole vault 112.

The triple line NNN is a time weighted moving average of non-event data.Non-event data are data collected when the alarm trigger state was“AS0.” Time weighting assigns lessor weights to older data points. Timeweighting factors are determined statistically. For computationalefficiency, those data points collected when the alarm trigger state was“AS0” with time weightings below a threshold value (e.g., determinedbased on sensor experience) are dropped from the moving average.

FIG. 8B is a subset of the data of FIG. 8A over a single 24 hour timeperiod on May 24, 2018. The y-axis has been enlarged and shows only arange of 400 ppm to 800 ppm. As mentioned above, the triple line NNNshows approximate sensor drift. Over the 24 hour period of FIG. 8B, thesensor drift is insignificant and the triple line NNN has a slope thatis essentially zero. Thus, FIG. 8B illustrates a time period duringwhich variations in the data were primarily caused by something otherthan sensor drift (referred to as “non-drift variations”). Non-limitingexamples of non-drift variations include stochastic variations withinthe sensor mechanism, stochastic variations within the hardware systemswhere analog signals are converted to digital signals, and natural andman-made perturbations to the analyte or property being measured.Man-made perturbations may include, for example, a running car parkedover a manhole cover, which will perturb the level of CO₂ inside themanhole upward (or increase the level of CO₂) until the car drives away.During this same time period, the aforementioned non-drift variationsyield sensor readings between about 600 ppm and 725 ppm. The upper andlower confidence bounds UB and LB are established by a maximumlikelihood estimate or similar statistical technique and provide adefined level of confidence that a value outside those bounds is quiteunlikely (e.g., less than 5% or perhaps less than 1%) to be caused bydrift or non-drift variations, but rather is very likely (e.g. greaterthan 95% or perhaps greater than 99%) a perturbation worthy ofcorroboration.

For example, the upper and lower confidence bounds UB and LB may bedetermined by adding and subtracting a noise threshold from an averagesensor reading. The average sensor reading and a standard deviation maybe determined for the sensor from historical sensor readings.Additionally, the upper and lower confidence bounds UB and LB may bedetermined from percentile values and/or upper-tile averages ondistributions that are highly skewed. New sensor readings fallingbetween the upper and lower confidence bounds UB and LB are identifiedas noise. The historical sensor readings include a number of pastsamples collected over a past time period. The past time period andnumber of past samples depends on the characteristics of the sensor andthe environment in which it operates. Typically sensor measurements arerecorded every 15 minutes and, thus, about 96 measurements are recordedevery day. The past time period may include one day, two days, or more.The noise threshold may be determined by the System Controller 190 usingmaximum-likelihood statistics or similar means to achieve a user-definedprobability threshold. By way of non-limiting examples, 90%, 95%, and99% may be used as user-defined probability thresholds. Thus, the noisethreshold may include all values that are statistically within a userselected confidence interval (e.g., 90%, 95%, and 99%) of the averagesensor reading. Older measurements in the historical sensor readings maybe weighted less than or equal to more contemporary measurements whenthe average sensor reading is calculated. Unequal weighting is mostappropriate where the sensor drift is mathematically significant overthe length of time chosen to calculate the average and standarddeviation.

Using the sample data of FIGS. 8A and 8B, it is clear that over anysingle day the drift is very small but, over the 63-day period, theimpact of the drift is about a factor of two. Thus, a 24-hour period isabout right to determine a baseline, the average sensor reading, and thestandard deviation for this sensor. Longer time periods can improve thestatistical veracity of the estimations. Therefore, an appropriate timeperiod to calculate the baseline, the average sensor reading, and thestandard deviation for this sensor in this environment may be about 24hours to 48 hours. Longer times are possible, but including morehistorical data provides diminishing returns of statistical veracity andsuffers from additional computational demands.

While the triple line NNN, the upper confidence bound UB, and the lowerconfidence bound LB shown in FIG. 8B appear to be horizontal because ofthe scale choice, they in fact each have a small positive slope, ΔC/Δt.For example, the average slope from FIG. 8A over the 63 day time periodis the difference between about 1200 ppm (on July 11^(th)) and about 700ppm (on May 10^(th)) divided by 63 days, which is about 7.9 ppm/day.Inspection of FIG. 8A for the 24 hour time period illustrated in FIG. 8Breveals that the slope on May 24^(th) is less than 7.9 ppm/day. Thedrift slope can be used to refine an anticipated data point, but such arefinement is generally unnecessary as the noise exemplified in FIG. 8Bis generally much greater than the drift. In the 24 hour periodillustrated in FIG. 8B, the span of the noise is about 125 ppm or morethan an order of magnitude greater than the drift.

Component Mass Balance

As mentioned above, a component mass balance may be used in block 206-K(see FIG. 7K) of the calculate method 200-K (see FIG. 7K) to determine aFGA rate and/or in block 242-K (see FIG. 7K) of the calculate method200-K (see FIG. 7K) to determine a burn rate.

For brevity in the discussion that follows, all input values andestimates are described as single deterministic values. Of course, allmeasurements are estimates of reality and all estimates include error.Therefore, probabilistic inputs may be used for each input described indeterministic terms below and a Monte Carlo simulation of those inputsmay be used to provide probabilistic outputs. This probabilisticapproach allows the end user of the information to judge the voracity ofthe results. For example, both a deterministic percentage lowerexplosive limit (“% LEL”) and a probabilistic % LEL may be determined. %LEL is a fraction of flammable components relative to that fractionwhich would support an explosion. If the deterministic % LEL isdetermined to be 75%, the user might take comfort that an explosion isunlikely. However, if the same result were reported probabilistically as75% MLE (maximum likelihood estimate) with 95% confidence levels at 71%(lower) and 103% (upper), the user is more likely to have a higher levelof alarm and make a better decision.

Referring to FIG. 1, even if the absolute output values of the firedetection sensor(s) 216 (see FIG. 3) are reliable, the dynamics of thesesystems are indeterminate. With passive ventilation, the flow of gasesin and out of the underground vault 112 is practically unknowable. Onlywith active ventilation, where the exhaust flow rate can be measured orestimated and the concentrations of the analytes in the exhaust can bemeasured or estimated, is it possible to perform a robust component massand energy balance on the vault environment. The mass balance allows anassessment of the size of a fire or other source of dangerous gases. Forexample, a smoldering cigarette would be of little concern, but a firethat is consuming 100 grams of polymer per minute would constitute asubstantial event. The former requires no action while the later demandsimmediate action to protect the public.

The System Controller 190 may use component mass balance to determineone or more of the following:

-   -   1. relevant alarm condition(s);    -   2. the alarm state level for an associated alarm condition;    -   3. the lower explosive limit (“LEL”) of the mixture of flammable        gases in air;    -   4. a corrected lower explosive limit (“CLEL”) of the mixture of        flammable gases that accounts for an abundance of non-flammable        gases introduced by oxidative decomposition;    -   5. anticipated dilution of O₂ and N₂;    -   6. an amount of energy being dissipated by active ventilation;        and    -   7. an amount of water being transported from the vault 112 by        evaporation.

Regarding determining relevant alarm condition(s), manhole events mayinclude oxidative decomposition, pyrolysis, and/or plasmatization. Thecomponent mass balance allows the event to be labeled. The benefit ofthis knowledge may be critical to respond properly to the manhole event.For example, oxidative decomposition is exothermic and potentiallyself-sustaining, meaning it requires different intervention thanpyrolysis and plasmatization, which are endothermic and can be halted byshutting the power off to burning equipment.

Regarding determining the alarm state level for an associated alarmcondition, the System Controller 190 may use component mass balance todetermine the size of a combustion event. Large events have greaterurgency than smaller events and very small events would representnuisance alarms (or an alarm where no action is required.)

FIG. 18 illustrates how various burning (oxidative decomposition andpyrolysis) cases can create flammable atmospheres in vaults. Thelogarithmic x-axis is burn rate expressed in grams per minute. They-axis is the gas mixture concentration expressed as a percentage of theCLEL ( % CLEL). Ignition and explosion are not possible until the % CLELis greater than 100%. The LEL (by definition in air) of a mixture offlammable gases is calculated using Equation 9 (below), which is LeChatelier's formula:

1/LEL_(mix) =c ₁/LEL₁ +c ₂/LEL₂ +c ₃/LEL₃ + . . . +c _(n)/LEL_(n)   (9)

In Equation 9, variables c₂, c₃, c_(n) are mole fractions of n componentgases in the mixture having lower explosive limits of LEL₁, LEL₂, LEL₃,. . . , LEL_(n) respectively. The sum of the mole fractions, c₂, c₃, . .. , c_(n), is unity.

The mixture LEL (i.e., LEL_(mix)) is corrected for dilution by inertgases above the levels found in the atmosphere by Equation 10 (below),which is Kondo's equation (S. Kondo, K. Takizawa, A. Takahashi, K.Tokuhashi, “Extended Le Chatelier's formula for carbon dioxide dilutioneffect on flammability limits,” Journal of Hazardous Materials A138(2006) 1-8):

c _(mix)/CLEL=c _(mix)/LEL_(mix) +p·(1−c _(mix))   (10)

In Equation 10, variable c_(mix) is the mole fraction of the flammablegases in the fuel-inert gas mixture, variable CLEL is the mixture LELcorrected for the inert gases (e.g. CO₂, H₂O) in excess of normalatmospheric inert gases, variable LEL_(mix) is the LEL of the mixture inair, and variable p is an experimentally determined parameter with atypical value of about −0.01.

In FIG. 18, the dependent variable is plotted for each burn rate, eachfire type, and a specified exhaust rate. A dotted line 950(corresponding to H₂ max pyrol; 0.1 m³/s ΔH_(f)=28 kJ/m) and a dashedline 952 (corresponding to H₂ max pyrol; 0.2 m³/s ΔH_(f)=28 kJ/m)demonstrate a hypothetical worst-case scenario where 100% of thehydrogen in the polymer is pyrolyzed to H₂. In the first case shown bythe dotted line 950, active ventilation is exhausting 0.1 m³/sec and, inthe second case shown by the dashed line 952, the exhaust is doubled.This hypothetical worst-case scenario is not possible because suchpyrolysis cannot occur until temperatures are about 500° C. Suchtemperatures are not possible (because emergency overload designtemperatures for electrical equipment are less than 200° C.) without anoxidative combustion process, because pyrolysis is endothermic. For eachcase in FIG. 18, a legend 960 includes the approximate net heat offormation (ΔH_(f)) for the burn. Positive values are endothermic andcannot sustain; negative values are exothermic and are potentiallysustainable in the duct-vault environment. The aforementioned dotted anddashed lines 950 and 952 are entirely hypothetical. Four solid compoundlines 971-974 illustrate where combustion and pyrolysis are mixed from20% to 90% oxidation. The solid compound lines 971-974 illustrate 20%oxidation, 50% oxidation, 80% oxidation, and 90% oxidation respectively.Each of the solid compound lines 971-974 depicts an example withnegative (favorable) net heat of formation and represents a realisticburn scenario.

To distinguish nuisance fires from fires of consequence, consider someexamples. A smoking cigarette weights about 1 gram and is consumed inabout 5 minutes. Its burn rate is thus about 0.2 g/min. A cigarette in avault is obviously a nuisance. A typical candle burns about 0.1 g/minand hence 100 candles would yield 10 g/min. Thus, even 100 candles donot have a significant burn rate. On the other hand, a typical autotraveling at 60 mph consumes about 119 g/min. This value is illustratedwith a vertical line 976 labeled “119 Auto @60” in FIG. 18. The exampleautomobile is consuming considerable fuel and, therefore, may beconsidered a fire of consequence.

A fire having a burn rate of 100 g/m in or greater is a pretty seriousfire. On the other hand, burn rates that are less than 1 g/min can belargely ignored unless they persist for long periods or grow with time.The character of a fire has a large impact on its severity. For example,fires with high oxidative character are much less likely to lead to anexplosion. Vault owners will want to deal with large fires in any case.One of ordinary skill in the art would recognize that the size of thefire (or its pyrolysis-burn rate) and the oxidative character of thefire impact both the % LEL and likelihood of an explosion.

Regarding an amount of energy being dissipated by active ventilationvault, owners are faced with equipment that ages at least partiallybased upon the temperature at which the equipment operates. As a generalrule of thumb, each 10° C. of temperature doubles the rate of oxidationor aging. Understanding how much energy is dissipated by activeventilation allows the vault owner to adjust their expectations forscheduled maintenance of equipment.

Regarding determining anticipated dilution of O₂ and N₂, when it isdesirable to dilute potentially explosive gases within the undergroundvault 112, dilution of the first type may be used to exhaust theinternal atmosphere 124 up to the maximum exhaust rate. Atmosphericallyrich components O₂ and N₂ decrease in concentration by dilution whenthere is an increase in combustion by-products or an increase inflammable gases by dilution. The magnitude of the dilution can beestimated when the exhaust rate is known. Performing a component massbalance (discussed below) yields the anticipated dilution of O₂ and N₂.

Regarding determining an amount of water being transported from thevault 112 by evaporation, there are reliability and convenience benefitsin keeping manholes dry. In conjunction with water level measurement,the effectiveness of water control features can be evaluated.

FIG. 19 illustrates typical evolution of a manhole event from initiationto extinguishment. Events in a manhole generally follow a somewhatpredictable progression with time. As a non-limiting example of such aprogression and using a secondary network as an example, a manhole eventmost likely starts as surface tracking on a old/damaged cable. During afirst phase 982, the predominate mechanism is plasmatization, whichcreates compounds like NO, NO₂, and O₃. Of course, the temperature ofplasma is 30,000° F. so some pyrolysis and oxidation also occur.Plasmatization and pyrolysis are both endothermic so they cannot grow ormaintain themselves without oxidation. At this stage of the fire, oxygenis plentiful in the duct. Oxidation creates carbon dioxide and water, isexothermic, and is a prerequisite for a growing fire. A second phase 984begins when oxidative decomposition becomes self-sustaining. This secondphase continues as the fire grows until the fresh supply of oxygen isexhausted. A third phase 986 is represented by a plateau 988. Theplateau 988 represents the maximum burn rate based upon the amount ofoxygen available. A fourth phase 990 occurs when the vault owner shutspower off to the circuit. The plasmatization has been marked bystochastic behavior as electrical paths are destroyed and reinitiatedduring the event. Once the power is turned off, plasmatizationterminates immediately. With less energy supplied to the event, a smalldecrease in the plateau 988 may occur. A fifth phase 992 of the eventwill not occur until an extinguishing medium is introduced or thepolymer is entirely consumed. During this fifth phase 992 the firesubsides. Knowing where a particular manhole event is along this eventdevelopment continuum allows the circuit owner to take appropriateaction—urgent or not so urgent.

FIG. 9 is a flow diagram of a method 300 of conducting a component massbalance that may be performed by the System Controller 190. Componentmass balance may be used to calculate flows into and out of theunderground vault 112. Active ventilation allows the underground vault112 to be considered a continuous stirred tank (“CST”). The exhaust flowF_(E) equals the fresh air flow F_(FA) of gases and particulates fromthe external atmosphere 122, the connection(s) flow F_(C) of gases andparticulates into the internal atmosphere 124 from another source (e.g.,one or more connections 118A-118J connected to the underground vault112), the evaporation flow F_(V) of evaporating liquids, and a change inwater depth (referred to as ΔDepth_(water)). Thus, this relationship maybe described using Equation 11, which is a total gaseous mass balanceequation:

F _(E) =F _(FA) +F _(C) +F _(V)+ΔDepth_(water)   (11)

Each value in the total gaseous mass balance equation is expressed ingaseous mass (or equivalent for water depth) per unit time. The SystemController 190 may estimate the change in water depth (referred to asΔDepth_(water)) with time using data received from the water levelsensor 214. Influx of water is positive flow and outflow is negativeflow. The System Controller 190 may estimate a volume of air displacedby the water influx. Failure to calculate ΔDepth_(water) would create anerror in the overall mass balance. The change in water depth is oftennegligible and may be ignored in many cases. However, in some vaultsnear sea coasts, tidal conditions create twice daily flooding andreverse flooding of vaults that should not be ignored.

The connection(s) flow F_(C) includes net gas flows from a fireregardless of where the fire is located. There is much more cablelocated within the connections 118A-118J connected to the vaults 112-116than there is cable in the vaults, and hence the connection(s) flowF_(C) is most likely from one of the connections. However, the fire mayalso originate in one of the vaults 112-116. For the purpose of thiscomponent mass balance, where the fire is located (e.g., in one of theconnections 118A-118J or vaults 112-116) is a distinction without adifference.

In first block 310, the System Controller 190 obtains vault parameters.By way of a non-limiting example, the System Controller 190 may performa method 350 (see FIG. 10) to obtain the vault parameters. In thisexample, the vault parameters include a dry vault volume and anatmospheric pressure.

In block 320, the System Controller 190 obtains exhaust flow parametersfor the exhaust flow F_(E). By way of a non-limiting example, the SystemController 190 may perform a method 400 (see FIG. 11) to obtain theexhaust flow parameters. In this example, the exhaust flow parametersinclude the following:

-   -   1. an exhaust flow rate,    -   2. an exhaust temperature value T_(E),    -   3. a vault turnover (e.g., in seconds), and    -   4. exhaust component parameters.        The exhaust component parameters may include one or more of the        following values for each component of the exhaust flow F_(E):    -   1. Concentration of the exhaust component (see second column of        Table B); and    -   2. Mass flow rate (g/s) of the exhaust component (see rightmost        column of Table B).        For example, if the exhaust flow rate is about 0.047 m³/s, the        exhaust temperature value T_(E) is about 25° C. (77° F.), and        turnover is about 428 seconds, Table B lists exemplary exhaust        component parameters.

TABLE B Component Volume Unit mole/m³ Mass (g/m³) Mass (g/s) O₂ 20.81% v8.507291 272.21631 12.84589 CO₂ 4,000 ppm 0.163496 7.19547 0.33955 CO 40ppm 0.001635 0.04580 0.00216 H₂O 20,945 ppm 0.856103 15.42294 0.72781(RH = 0.67) H₂S — ppm 0.000000 0.00000 0.00000 SO₂ — ppm 0.0000000.00000 0.00000 VOC (CH₄) 178 ppm 0.007276 0.11670 0.00551 NO 7 ppm0.000286 0.00859 0.00041 NO₂ 17 ppm 0.000695 0.03197 0.00151 O₃ 11 ppm0.000450 0.02158 0.00102 H₂ 64 ppm 0.002606 0.00525 0.00025 N₂  76.7% v31.334221 877.77806 41.42235 Soot (C) 38 μg/m³ 0.000003 0.00004 0.00000Ash (SiO₂) — μg/m³ 0.00000 Total:   100% v 40.874 1172.84 55.34644

In block 330, the System Controller 190 obtains fresh air flowparameters for the fresh air flow F_(FA). By way of a non-limitingexample, the System Controller 190 may perform a method 500 (see FIG.12) to obtain the fresh air flow parameters. In this example, the freshair flow parameters include the following:

-   -   1. a fresh air flow rate,    -   2. a fresh air temperature value T_(FA), and    -   3. fresh air component parameters.        The fresh air component parameters may include one or more of        the following values for each component of the fresh air flow        F_(FA):    -   1. Concentration of the fresh air component (see second column        of Table C); and    -   2. Mass flow rate (g/s) of the fresh air component (see        rightmost column of Table C).        For example, if the fresh air flow rate is about 0.0463981 m³/s        and the fresh air temperature value is about 25° C. (77° F.),        Table C lists exemplary fresh air component parameters.

TABLE C Component Volume Unit mole/m³ Mass (g/m³) Mass (g/s) O₂ 20.81% v8.5072913 272.21631 12.63033 CO₂ 400 ppm 0.0163496 0.71955 0.03339 CO 4ppm 0.0001635 0.00458 0.00021 H₂O 15,631 ppm 0.638883 11.5097 0.53403(RH = 0.5) H₂S — ppm 0.000000 0.0000 0.00000 SO₂ — ppm 0.000000 0.00000.00000 VOC (CH₄) 22 ppm 0.000899 0.0144 0.00067 NO — ppm 0.0000000.0000 0.00000 NO₂ — ppm 0.000000 0.0000 0.00000 O₃ — ppm 0.0000000.0000 0.00000 H₂ — ppm 0.000000 0.0000 0.00000 N₂  77.6% v 31.710472888.3181 41.21631 Soot (C) — μg/m³ 0.000000 0.0000 0.00000 Ash (SiO₂) —μg/m³ 0.000000 0.0000 0.00000 Total:   100% v 40.874058 1172.78264154.41494

In block 340, the System Controller 190 obtains connection(s) flowparameters for the connection(s) flow F_(C). By way of a non-limitingexample, the System Controller 190 may perform a method 600 (see FIG.13) to obtain the connection(s) flow parameters. In this example, theconnection(s) flow parameters the following:

-   -   1. a connection(s) flow rate,    -   2. a connection(s) temperature value T_(C), and    -   3. connection(s) component parameters.

The connection(s) component parameters may include one or more of thefollowing values for each component of the connection(s) flow F_(C):

-   -   1. Concentration of the connection(s) component (see third        column of Table D); and    -   2. Mass flow rate (g/s) of the connection(s) component (see        fourth column of Table D).        For example, if the connection(s) flow rate is about 0.000226        m³/s and the connection(s) temperature value is about 25° C.        (77° F.), Table D lists exemplary connection(s) component        parameters.

TABLE D Mass Mass Polymer Component Volume (m³/s) (%) (g/s) (mol/s) O₂0.000000113  0.038% 0.000125 CO₂ 0.00020  93.508% 0.306169 0.00695680 CO0.000002  0.595% 0.001949 0.00006957 H₂O 0.00001  3.126% 0.0102356 (RH= 1) H₂S 0.00000 0.00000% 0.0000000 SO₂ — 0.00000% 0.0000000 VOC (CH₄)0.00001 1.47755% 0.0048379 0.00030161 NO 0.00000 0.12375% 0.0004052 NO₂0.00000 0.46073% 0.0015085 O₃ 0.00000 0.31103% 0.0010184 H₂ 0.000000.07585% 0.0002483 N₂ 0.00000 0.28291% 0.0009263 Soot (C) 0.000000.00055% 0.0000018 0.00000015 Ash (SiO₂) — 0.00000% 0.0000000 Total:0.00023 100.000% 0.3274247 0.0073281

Determining the connection(s) flow parameters requires the fresh airflow parameters and vice versa. Thus, as will be described below,portions of blocks 330 and 340 may be performed together. For example,the connection(s) and fresh air flow parameters may be determinediteratively using a method well known in the art, such as directsubstitution, Newton-Raphson, and the like. Using such a method, a massbalance error value may be driven to zero by adjusting the fresh airflow rate. The mass balance error value may be equal to a sum of themass flow rate of the exhaust components (e.g., last row in rightmostcolumn of Table B) minus a sum of the mass flow rate of the fresh aircomponents (e.g., last row in rightmost column of Table C) and a sum ofthe mass flow rates of the connection(s) components (e.g., last row infourth column of Table D).

In block 342, the System Controller 190 performs an energy balance andcalculates enthalpies (a first exhaust value “h_(e),” a second fresh airvalue “h_(f),” and a third connection(s) value “h_(c)”) and energyexhausted “Δh” for each of the components shown in the leftmost columnsof Tables B-D. By way of a non-limiting example, the energy balance maybe implemented by a method 700 (see FIG. 14).

In block 344, the System Controller 190 calculates a rate of net waterremoval “Δw” by the evaporation F_(V). By way of a non-limiting example,the rate of net water removal “Δw” may be calculated using a method 800(see FIG. 15).

In block 348, the System Controller 190 provides (e.g., displays) avalue of interest. For example, the connection(s) flow F_(C) may includenitrogen dioxide as a connection(s) component. The connection(s)component parameters for the nitrogen dioxide may be provided as ametric of the size of a combustion event. Thus, these parameters may beused to determine alarm state level for an associated alarm condition.For example, the System Controller 190 may provide the burn rate and/orthe FGA.

By way of another example, the connection(s) components of theconnection(s) flow F_(C) may include soot. The connection(s) componentparameters for the soot may be provided as a metric of an amount ofenergy being dissipated by active ventilation. For example, the energyexhausted “Δh” calculated for soot using the energy balance of themethod 700 (see FIG. 14) may be used as a metric of the amount of energydissipated by active ventilation.

By way of another example, the System Controller 190 may provide therate of net water removal “Δw” by the evaporation F_(V) calculated inblock 344.

By way of another example, the System Controller 190 may provide one ormore of the enthalpies (e.g., the first exhaust value “h_(e)”, thesecond fresh air value “h_(f)”, and the third connection(s) value“h_(c)”) and/or the energy exhausted “Δh” for at least one of thecomponent of the flows F_(E), F_(FA), and F_(C).

Then, the method 300 terminates.

FIG. 10 is a flow diagram of the method 350 of determining vaultparameters performed by the System Controller 190. In first block 360,the System Controller 190 obtains a dry vault volume of the vault 112.For example, the System Controller 190 may estimate the dry vault volumeby multiplying a vault length by a vault width and a vault height. TheSystem Controller 190 may add a chimney volume, if present, to the dryvault volume. If the chimney is generally cylindrical in shape and has aheight “h” and a radius “r,” the chimney volume may be calculated as thevolume of a cylinder, which may be calculated with the formula h*πr².The System Controller 190 may subtract an equipment volume of theequipment 119 (e.g., cables, transformers, components, etc.), ifpresent, from the dry vault volume. If water is in the vault 112, theSystem Controller 190 may subtract a volume of water from the dry vaultvolume.

In block 370, the System Controller 190 obtains atmospheric pressureP_(atm). For example, the System Controller 190 may assume isobaricconditions and use an atmospheric pressure obtained from weather data,an atmospheric pressure obtained from one or more of the sensor(s) 128,or use 14.696 pounds per square inch, absolute (“psia”) as theatmospheric pressure.

In block 380, the System Controller 190 obtains parameter values to usewhen determining a water vapor saturation pressure value with sufficientaccuracy between 0° C. and 373° C. using a method described by W. Wagnerand A. Pruß, “The IAPWS Formulation 1995 for the ThermodynamicProperties of Ordinary Water Substance for General and Scientific Use,”Journal of Physical and Chemical Reference Data, June 2002 ,Volume 31,Issue 2, pp. 387535 (copy available athttps://www.vaisala.com/sites/defult/files/documents/Humidity_Conversion_Formulas_B210973EN-F.pdf).

The parameters values obtained in block 380 may include values forparameters “A,” “n,” and “T_(n).” The values of these parameters varydepending upon temperature. The parameter “A” may equal a first constant(e.g., 6.089613) if the temperature is less than 0° C. The parameter “A”may equal a second constant (e.g., 6.116441) if the temperature isgreater than or equal to 0° C. and less than 50° C. Otherwise, theparameter “A” may equal a third constant (e.g., 6.004918). Similarly,the parameter “n” may equal a first constant (e.g., 9.7787073) if thetemperature is less than 0° C. The parameter “n” may equal a secondconstant (e.g., 7.591386) if the temperature is greater than or equal to0° C. and less than 50° C. Otherwise, the parameter “n” may equal athird constant (e.g., 7.337936). Additionally, the parameter “T_(n)” mayequal a first constant (e.g., 273.1466) if the temperature is less than0° C. The parameter “T_(n)” may equal a second constant (e.g., 240.7263)if the temperature is greater than or equal to 0° C. and less than 50°C. Otherwise, the parameter “T_(n)” may equal a third constant (e.g.,229.3975). These values are summarized in Table E below.

TABLE E Parameter Temp < 0 0 <= Temp < 50 50 >= Temp A 6.089613 6.1164416.004918 n 9.7787073 7.591386 7.337936 T_(n) 273.1466 240.7263 229.3975

In block 390, the System Controller 190 obtains molecular weights foruse in calculations. For example, the System Controller 190 may obtain amolecular weight MWFS for a potential fuel source (e.g., one or morepolymers used to construct cable insulation) that may burn in theconnection(s) 118A-118J. By way of additional non-limiting examples, theSystem Controller 190 may obtain a molecular weight for each ofcomponents shown in the leftmost columns of Tables B-D.

Then, the method 350 terminates.

FIG. 11 is a flow diagram of the method 400 of determining flowparameters for the exhaust flow F_(E) that may be performed by theSystem Controller 190.

In first block 410, the System Controller 190 obtains an exhausttemperature value T_(E) for the exhaust flow F_(E) from one or more ofthe fire detection sensor(s) 216 (see FIG. 3).

In block 415, the System Controller 190 obtains a volumetric exhaustflow rate for the exhaust flow F_(E). For example, the System Controller190 may obtain the volumetric exhaust flow rate from the manhole eventsuppression system 140. For example, the System Controller 190 mayempirically correlate current drawn by the air moving device 132 to avolumetric exhaust flow rate. If the air moving device 132 isimplemented as a rotary fan, the System Controller 190 may empiricallycorrelate revolution-per-minute (“RPM”) of the fan and/or current drawnby the fan to the volumetric exhaust flow rate. By way othernon-limiting examples, the System Controller 190 may obtain thevolumetric exhaust flow rate from one or more of the fire detectionsensor(s) 216 (see FIG. 3) configured to measure volumetric flow and/orair velocity in the first section P1 of the ventilation pipe 148.

In block 420, the System Controller 190 calculates a turnover rate. Theturnover rate is the vault volume divided by the volumetric exhaust flowrate

In block 425, the System Controller 190 obtains a concentrationmeasurement for each of a plurality of exhaust components that may bepresent in the exhaust flow F_(E). Exemplary exhaust components arelisted in the left-most column of Table B (above) and exemplary exhaustconcentration measurements are provided in the second column labeled“Volume” of Table B.

The System Controller 190 may obtain concentrations of oxygen, carbondioxide, carbon monoxide, and the volatile organic compounds in theexhaust flow F_(E) from one or more of the fire detection sensor(s) 216(see FIG. 3). The System Controller 190 may obtain concentrations ofhydrogen sulfide and/or sulfur dioxide from one or more of the firedetection sensor(s) 216 (see FIG. 3) or assume each has a concentrationof zero. The System Controller 190 may obtain concentrations of nitrousoxide, nitrogen dioxide, and/or ozone from one or more of the firedetection sensor(s) 216 (see FIG. 3), assume each has a concentration ofzero, or assume each has a concentration equal to an amount of pollutionprovided by a third party. Optionally, the concentrations of nitrousoxide and/or nitrogen dioxide may be obtained by measuring aconcentration of NOx.

The System Controller 190 may obtain the concentration of hydrogen inthe exhaust flow F_(E) from the fire detection sensor(s) 216 or estimatethe concentration of hydrogen from the concentrations of carbon dioxide(CO₂) and carbon monoxide (CO) according to Equation 12 below:

H₂ =a·CO+b·CO₂   (12)

In Equation 12, the concentrations of carbon dioxide (CO₂) and carbonmonoxide (CO) may be equal to their respective amounts present in thefresh air. The variable “a” may equal 1.77 and the variable “b” mayequal 0, which were determined from experimental data.

The System Controller 190 may obtain the concentration of nitrogen inthe exhaust flow F_(E) by subtracting the concentrations of all otherexhaust components, expressed as a percentage, from 100%. The SystemController 190 may obtain the concentration of particulates and aerosolsin the exhaust flow F_(E) from one or more of the fire detectionsensor(s) 216 (see FIG. 3) and apportion between soot and ash (e.g.,based upon the fire type). If there is no fire, these values can beignored.

The System Controller 190 may obtain a relative humidity from one ormore of the sensor(s) 128 and use it to determine a concentration ofwater vapor in the exhaust flow F_(E). To determine the concentration ofwater vapor, the System Controller 190 may calculate a water vaporsaturation pressure “Pws_(E)” for the exhaust flow F_(E) using Equation13 below:

Pws _(E) =A*10^(((m*TE)/(TE+Tn)))   (13)

In Equation 13 above, the values of the parameters “A,” “m,” and “T_(n)”are taken from Table E for the exhaust temperature value T_(E). Then,the System Controller 190 may calculate a water vapor pressure Pw_(E)for the exhaust flow F_(E) using Equation 14 below:

Pw _(E) =Pws _(E)*RH*100   (14)

Next, the System Controller 190 may calculate a water density WD_(E)(e.g., in g/m³) using Equation 15 below:

WD_(E)=2.16679*Pw _(E)/(T _(E)+273.15)   (15)

Finally, the System Controller 190 may calculate the water vaporconcentration (e.g., ppm) for the exhaust flow F_(E) using Equation 16below.

W _(E)=1,000,000*(WD_(E)/MWW)*0.00008205745*(T _(E)+273.15)/P_(atm)  (16)

In Equation 16 above, a variable MWW is the molecular weight of waterand the variable “P_(atm)” is atmospheric pressure (measured inatmospheres).

In optional block 430, if the exhaust components are not expressed inmass per unit volume (e.g., g/m³), the System Controller 190 convertsthem. For example, if the concentrations of the exhaust components areexpressed as volume-percent at absolute pressure, the System Controller190 may convert them to moles per unit volume (see fourth column ofTable B) using the exhaust temperature value T_(E) and the ideal gaslaw. Then, the System Controller 190 may use the molecular weight ofeach component to convert the moles per unit volume to mass per unitvolume (see fifth column of Table B). By way of a non-limiting example,the mass may be expressed as grams (“g”) and the unit volume may be acubic meter (m³) shown in the fifth column of Table B).

In block 435, the System Controller 190 totals the exhaust components(e.g., expressed in g/m³) to obtain an exhaust total (see last row offifth column of Table B).

In block 438, the System Controller 190 may utilize the component volumeand molar flow rates to calculate mixture lower explosive limits (i.e.,LEL_(mix)) and mixture corrected lower explosive limits (i.e.,CLEL_(mix)).

In optional block 440, the System Controller 190 may divide the mass perunit volume of each of the exhaust components by the exhaust total toobtain exhaust percentages.

In block 445, the System Controller 190 multiplies the mass per unitvolume of each of the exhaust components (e.g., expressed in g/m³) bythe exhaust flow rate (expressed in m³/s) to obtain exhaust componentmass flow rates (e.g., g/s) shown in the rightmost column of Table B.

In block 450, the System Controller 190 totals the exhaust componentmass flow rates to obtain a total exhaust component flow rate (e.g.,g/s) shown in last row of rightmost column of Table B.

Then, the method 400 terminates.

FIG. 12 is a flow diagram of the method 500 of determining flowparameters for the fresh air flow F_(FA) that may be performed by theSystem Controller 190.

In first block 510, the System Controller 190 obtains a fresh airtemperature value T_(FA) from one or more of the fire detectionsensor(s) 216 (see FIG. 3) and/or real-time weather data.

In block 515, the System Controller 190 obtains an estimated fresh airflow rate for the fresh air flow F_(FA). As mentioned above, the SystemController 190 may adjust the fresh air flow rate until the mass balanceerror value is zero.

In block 525, the System Controller 190 obtains a concentrationmeasurement for each of a plurality of fresh air components that may bepresent in the fresh air flow F_(FA). Exemplary fresh air components arelisted in the left-most column of Table C (above) and exemplary freshair concentration measurements are provided in the second column labeled“Volume” of Table B.

The System Controller 190 may obtain the concentration of oxygen (O₂) inthe fresh air flow F_(FA) from one or more of the fire detectionsensor(s) 216 (see FIG. 3), from a third party data source, and/or use atypical tropospheric level adjusted for known variations ofnon-nitrogen, non-oxygen components. For example, the System Controller190 may express the fresh air components as a percentage of the freshair flow F_(FA), subtract all components that are not nitrogen or oxygenfrom 100%, and multiply the difference by a percentage of oxygen that istypical in the troposphere.

The System Controller 190 may obtain the concentration of carbon dioxide(CO₂) in the fresh air flow F_(FA) from one or more of the firedetection sensor(s) 216 (see FIG. 3), from a third party data source,and/or use a typical tropospheric level adjusted for known variations ofnon-nitrogen, non-oxygen components.

The System Controller 190 may obtain the concentration of carbonmonoxide (CO) in the fresh air flow F_(FA) from one or more of the firedetection sensor(s) 216 (see FIG. 3), from a third party data source,and/or use a typical local level.

The System Controller 190 obtains the relative humidity “RH” of thefresh air flow F_(FA) from one or more of the fire detection sensor(s)216 (see FIG. 3), from a third party data source, and/or use a typicalseasonal and/or local level. The System Controller 190 uses the relativehumidity “RH” of the fresh air flow F_(FA) to calculate the water vaporconcentration (e.g., ppm). To do so, the System

Controller 190 may calculate a water vapor saturation pressure“Pws_(FA)” for the fresh air flow F_(FA) using Equation 17 below:

Pws _(FA) A*10^(((m*TFA)/(TFA+Tn)))   (17)

In Equation 17 above, the values of the parameters “A,” “m,” and “T_(n)”are taken from Table E for the fresh air temperature value T_(FA). Then,the System Controller 190 may calculate a water vapor pressure Pw_(FA)for the fresh air flow F_(FA) using Equation 18 below:

Pw _(FA) =Pws _(FA)*RH*100   (18)

Next, the System Controller 190 may calculate a water density WD_(FA)(e.g., in g/m³) using Equation 19 below:

WD_(FA)=2.16679*Pw _(FA)/(T _(FA)+273.15)   (19)

Finally, the System Controller 190 may calculate the water vaporconcentration (e.g., ppm) for the fresh air flow F_(FA) using Equation20 below.

W _(FA)=1,000,000*(WD_(FA)/MWW)*0.00008205745*(T _(FA)+273.15)/P _(atm)  (20)

In Equation 20 above, the variable MWW is the molecular weight of waterand the variable “P_(atm)” is atmospheric pressure (measured inatmospheres).

The System Controller 190 may obtain the concentration of each ofhydrogen sulfide, sulfur dioxide, VOCs, nitrous oxide, nitrogen dioxide,and ozone in the fresh air flow F_(FA) from one or more of the firedetection sensor(s) 216 (see FIG. 3), from a third party data source, orassume the concentration is zero.

The System Controller 190 may assume the concentration of hydrogen (H₂)in the fresh air flow F_(FA) is zero.

The System Controller 190 may estimate the concentration of nitrogenusing the typical tropospheric level adjusted for known variations ofnon-nitrogen, non-oxygen components. For example, the System Controller190 may express the fresh air components as a percentage of the freshair flow F_(FA), subtract all components that are not nitrogen or oxygenfrom 100%, and multiply the difference by a percentage of nitrogen thatis typical in the troposphere.

The System Controller 190 may obtain the concentration of soot (orparticulates) in the fresh air flow F_(FA) from one or more of the firedetection sensor(s) 216 (see FIG. 3) and/or a third party data source(e.g., pollution data).

The System Controller 190 may assume the concentration of ash in thefresh air flow F_(FA) is zero.

In optional block 530, if the fresh air components are not expressed inmass per unit volume (e.g., g/m³), the System Controller 190 convertsthem. For example, if the concentrations of the fresh air components areexpressed as volume-percent at absolute pressure, the System Controller190 may convert them to moles per unit volume (see fourth column ofTable C) using the fresh air temperature value T_(E) and the ideal gaslaw. Then, the System Controller 190 may use the molecular weight ofeach component to convert the moles per unit volume to mass per unitvolume (see fifth column of Table C). By way of a non-limiting example,the mass may be expressed as grams (“g”) and the unit volume may be acubic meter (m³) shown in the fifth column of Table C).

In block 535, the System Controller 190 totals the mass per unit volumeof the fresh air components (e.g., expressed in g/m³) to obtain a freshair total (see last row of fifth column of Table C).

In optional block 540, the System Controller 190 may divide the mass perunit volume of each of the fresh air components by the fresh air totalto obtain fresh air percentages.

In block 545, the System Controller 190 multiplies the mass per unitvolume of each of the fresh air components (e.g., expressed in g/m³) bythe fresh air flow rate (expressed in m³/s) to obtain fresh aircomponent mass flow rates (e.g., g/s) shown in the rightmost column ofTable C.

In block 550, the System Controller 190 totals the fresh air componentmass flow rates to obtain a total fresh air component flow rate (e.g.,g/s) shown in last row of rightmost column of Table C.

Then, the method 500 terminates.

If there is no fire in the system 100 (see FIG. 1), the concentrations(shown in the second column of Table B) of each of the exhaustcomponents are equal to the concentrations (shown in the second columnof Table C) of the fresh air components. However, if a fire is present,these concentrations will not be equal. In other words, the evaporationflow F_(V) and/or the connection(s) flow F_(C) is/are contributing tothe exhaust flow F_(E).

FIG. 13 is a flow diagram of the method 600 of determining flowparameters for the connection(s) flow F_(C) that may be performed by theSystem Controller 190 (e.g., when these concentrations are not equal).

In first block 610, the System Controller 190 obtains a connection(s)temperature value T_(C). The System Controller 190 may obtain theconnection(s) temperature value T_(C) from one or more of the firedetection sensor(s) 216 (e.g., a thermistor, an infrared sensor, and thelike). Alternatively, the System Controller 190 may estimate theconnection(s) temperature value T_(C) from cable load data and/or heatof combustion, when present. By way of another non-limiting example, theSystem Controller 190 may assume the connection(s) temperature valueT_(C) is the same as the exhaust temperature value T_(E).

In block 615, the System Controller 190 obtains an estimated connectionflow rate for the connection(s) flow F_(C). As mentioned above, theSystem Controller 190 determines the connection(s) flow rate byadjusting the fresh air flow rate until the mass balance error value iszero.

In block 620, the System Controller 190 estimates component mass flowrates (shown in the fourth column of Table D above) for at least some ofthe connection(s) components. For example, the component mass flow ratesof the carbon dioxide (CO₂), carbon monoxide (CO), hydrogen (H₂), sulfurdioxide (SO₂), VOCs, nitrous oxide (NO), nitrogen dioxide (NO₂), ozone(O₃), Soot, and ash may be obtained by subtracting their respectivecomponent mass flow rates in the fresh air flow F_(FA) from theirrespective component mass flow rates in the exhaust flow F_(E).

The System Controller 190 may use the component mass flow rate of carbondioxide to estimate a first (CO₂ based) rate at which moles of a polymerconsumed (shown in in the third row of the rightmost column of Table Dabove). Oxidative decomposition of a single repeating polymer unityields a single molecule of carbon dioxide. Therefore, the first (CO₂based) rate (e.g., expressed as moles/second) at which the polymerconsumed by oxidative decomposition is approximately equal to thecomponent mass flow rate of carbon dioxide divided by the molecularweight of carbon dioxide.

The System Controller 190 may use the component mass flow rate of carbonmonoxide to estimate a second (CO based) rate at which moles of apolymer consumed (shown in the fourth row of the rightmost column ofTable D above). Oxidative decomposition (with insufficient oxygen forcomplete combustion) of a single repeating polymer unit yields a singlemolecule of carbon monoxide. Thus, the second (CO based) rate (e.g.,expressed as moles/second) at which the polymer consumed by oxidativedecomposition is approximately equal to the component mass flow rate ofcarbon monoxide divided by the molecular weight of carbon monoxide.

Hydrogen is a pyrolysis product of polymers. If hydrogen is present inthe exhaust flow F_(E), the hydrogen likely came from pyrolysis.

Sulfur dioxide is a combustion product of hydrogen sulfide or sulfurused as curing agents or anti-oxidants in polymers. If any sulfurdioxide is present in the exhaust flow F_(E), the sulfur dioxide likelycame from combustion. Where hydrogen sulfide gas is ubiquitous, sulfurdioxide will accompany most combustion events. The System Controller 190may ignore the sulfur dioxide because sulfur concentration is low inpolymers.

The System Controller 190 may assume the VOCs are methane (CH₄). Ifrefined measurements are available for other hydrocarbons, the SystemController 190 may refine the analysis using the same method. The SystemController 190 may use the component mass flow rate of VOCs to estimatea third (CH₄ based) rate at which moles of a polymer consumed (shown inthe eighth row of the rightmost column of Table D above). Burning asingle repeating polymer unit yields a single molecule of methane.Therefore, the third (CH₄ based) rate (e.g., expressed as moles/second)is approximately equal to the component mass flow rate of VOCs dividedby the molecular weight of methane.

Nitrous oxide is formed as a result of many combustion events and isparticularly prevalent where plasmatization occurs and hence is a markerfor electrical arcing. It is not useful directly to estimate burn rate.

Nitrogen dioxide is formed as a result of many combustion events and isparticularly prevalent where plasmatization occurs. Therefore, nitrogendioxide is a marker for electrical arcing but is not useful directly toestimate burn rate.

Ozone is formed as a result of many combustion events and isparticularly prevalent where plasmatization occurs. Therefore, ozone isa marker for electrical arcing but is not useful directly to estimateburn rate.

Soot may be primarily carbon. A portion of soot is deposited on surfacesor settles and may not be measured in the exhaust flow F_(E). The SystemController 190 may ignore such carbon. Alternatively, the SystemController 190 may use the component mass flow rate of soot to estimatea fourth (soot based) rate at which moles of a polymer consumed (shownin the fourteenth row of the rightmost column of Table D above). Thefourth (soot based) rate (e.g., expressed as moles/second) isapproximately equal to the component mass flow rate of soot divided bythe molecular weight of carbon.

Ash may be primarily silicon dioxide.

Much of the water vapor produced as a result of combustion condenses.When the hot combustion products, including water vapor, enter the vault112, they cool to the temperature of the vault 112 and condense intoliquid water. The System Controller 190 ignores this liquid water.Therefore, the relative humidity RH is assumed to be 100% at the exhausttemperature value T_(E).

The System Controller 190 uses the relative humidity “RH” of theconnection(s) flow F_(C) to calculate the water vapor concentration(e.g., % of mass). To do so, the System Controller 190 may calculate awater vapor saturation pressure “Pws_(C)” for the connection(s) flowF_(C) using Equation 21 below:

Pws _(C) =A*10^(((m*TE)/(TE+Tn)))   (21)

In Equation 21 above, the values of the parameters “A,” “m,” and “T_(n)”are taken from Table E for the exhaust temperature value T_(E). Then,the System Controller 190 may calculate a water vapor pressure Pw_(C)for the connection(s) flow F_(C) using Equation 22 below:

Pw _(C) =Pws _(C)*RH* 100   (22)

In Equation 22 above, the relative humidity RH is one. Next, the SystemController 190 may calculate a water density WD_(C) (e.g., in g/m³)using Equation 23 below:

WD_(C)=2.16679*Pw _(C)/(T _(E)+273.15)   (23)

Finally, the System Controller 190 may calculate the water vaporconcentration (e.g., % of mass) for the connection(s) flow F_(C) usingEquation 24 below.

W _(C)=(WD_(C)/MWW)*0.00008205745*(T _(E)+273.15)/P _(atm)   (24)

In Equation 24 above, the variable MWW is the molecular weight of waterand the variable “P_(atm)” is atmospheric pressure (measured inatmospheres).

Then, the System Controller 190 may calculate the component mass flowrate of the water vapor based on the water vapor concentration.

The component mass flow rate of the oxygen (O₂) may be calculated basedon the component mass flow rates of the nitrogen (N₂), carbon dioxide,hydrogen, and carbon monoxide. Much available oxygen is consumed byoxidative decomposition. However, no combustion is perfect and someoxygen will always remain. To estimate the component mass flow rate ofoxygen (O₂) the System Controller 190 may multiply the component massflow rate of nitrogen by both first and second values. The first valueis atmospheric O₂ divided by atmospheric N₂ (e.g., 20.95/78.09). Thesecond value is the component mass flow rate of carbon monoxide (e.g.,expressed in moles per second) divided by the component mass flow rateof carbon dioxide (e.g., expressed in moles per second), one is added tothis quotient, and the sum is divided by two. Ample carbon dioxideindicates a sufficient supply of oxygen to support oxidativedecomposition. The presence of ample carbon monoxide indicates a dearthof oxygen.

The component mass flow rate of the hydrogen (H₂) may be measured by thefire detection sensor(s) 216 or calculated based on the component massflow rates of the carbon dioxide and carbon monoxide. In oxygen richaerobic environments, hydrogen evolution is close to zero. During hightemperature anaerobic pyrolysis, all of the hydrogen atoms in a polymerare converted to hydrogen gas. Most manhole events fall between thesetwo extremes. The System Controller 190 may calculate the component massflow rate of the hydrogen (H₂) using an aerobic estimate (e.g., about1.770834) and an anaerobic estimate (0). Then the System Controller 190multiplies the anaerobic estimate by the first (CO₂ based) rate and addsthis value to the aerobic estimate multiplied by the second (CO based)rate. Next, the System Controller 190 multiplies this value by themolecular weight of hydrogen (H₂) to obtain the component mass flow rateof the hydrogen (H₂).

The component mass flow rate of the nitrogen (N₂) may be calculatedbased on the component mass flow rates of the carbon dioxide, carbonmonoxide, nitrous oxide (NO), and nitrogen dioxide (NO₂). Each mole ofCO₂ and each two moles of CO entrain 3.727 moles of N₂. Thus, the SystemController 190 obtains a first value by adding the first (CO₂ based)rate to the second (CO based) rate divided by two. NO and NO₂ consumenitrogen in ratios of 1:1 and 1:2, respectively. Thus, the SystemController 190 obtains second and third values. The second value isobtained by subtracting from the first value the component mass flowrate of the nitrous oxide (NO) multiplied by the molecular weight of thenitrous oxide (NO). The third value is obtained by subtracting from thesecond value the component mass flow rate of the nitrogen dioxide (NO₂)multiplied by the molecular weight of the nitrogen dioxide (NO₂) anddivided by two. Oxidative decomposition entrains nitrogen with oxygen(N₂/O₂) in a volume and molar proportion of 78.09/20.95, respectively.Thus, the System Controller 190 obtains the component mass flow rate ofthe nitrogen (N₂) by multiplying the third value by 78.09/20.95 and themolecular weight of nitrogen (N₂).

In block 625, the System Controller 190 obtains a consumption rate bytotaling the first (CO₂ based), second (CO based), third (CH₄ based),and fourth (soot based) rates at which the polymer is consumed.

In block 630, the System Controller 190 estimates a burn rate for thepotential fuel source. The System Controller 190 may calculate the burnrate by multiplying the consumption rate by the molecular weight MWFS(e.g., about 14.03) of the potential fuel source. The burn rate may beexpressed in grams per minute or second. The burn rate estimated inblock 630 may be used as the burn rate in block 242-K (see FIG. 7K) ofthe calculate method 200-K (see FIG. 7K). Alternatively, where there isno fire, the burn rate estimated in block 630 may be used as the FGA inblock 206-K (see FIG. 7K).

In block 635, the System Controller 190 obtains an estimated temperatureincrease “ΔT” caused by the burn components reaching the vault 112. Forexample, the System Controller 190 may obtain the estimated temperatureincrease from one or more of the fire detection sensor(s) 216 (see FIG.3). The estimated temperature increase “ΔT” represents a temperatureincrease above the vault ambient temperature and is required to applythe ideal gas law to the connection(s) flow F_(C) to complete a robustenergy balance.

In block 640, the System Controller 190 may convert the component massflow rates (e.g., grams per second) to component volume flow rates(cubic meters per second) for each of the connection(s) components.Exemplary component volume flow rates are provided in the second columnof Table D above.

Then, the method 600 terminates.

FIG. 14 is a flow diagram of the method 700 of performing the energybalance. In first block 710, the System Controller 190 obtains a heatcapacity (e.g., expressed as joules per gram·° K) for each of theexhaust components (see leftmost column of Table B). The heat capacityfor each of the exhaust components may be found in relevant literature.

In next block 720, the System Controller 190 calculates the energyexhausted “Δh” (BTU/min or J/s) by each component. To do so, the SystemController 190 calculates the first exhaust value “h_(e)” by multiplyingthe heat capacity of the exhaust component by both the component massflow rate of the exhaust component and absolute temperature (e.g., theexhaust temperature value T_(E)+459.67). Then, the System Controller 190calculates, for each fresh air component, the second fresh air value“h_(f)” by multiplying the heat capacity of the fresh air component byboth the component mass flow rate of the fresh air component andabsolute temperature (e.g., the fresh air temperature valueT_(FA)+459.67). Next, the System Controller 190 calculates, for eachconnection(s) component, the third connection(s) value “h_(e)” bymultiplying the heat capacity of the connection(s) component by both thecomponent mass flow rate of the connection(s) component and absolutetemperature estimated above (e.g., the connection(s) temperature valueT_(C)+459.67). Finally, for each component, the System Controller 190subtracts both the third connection(s) value and the second fresh airvalue “h_(f)” from the first exhaust value “h_(e)” to obtain the energyexhausted “Δh” for the component. In other words, for each component,the energy exhausted “Δh” equals the first exhaust value “h_(e)” minusboth the fresh air value “h_(f)” and the third connection(s) value“h_(e)”.

Then, the method 700 terminates.

FIG. 15 is a flow diagram of the method 800 of calculating a rate of netwater removal “Δw” from the vault 112. It is desirable to keep water outof the vault 112. When the vault 112 does not experience tidal inflowsand outflows of water, water can depart the vault 112 in four ways: (a)leak/diffuse through the concrete, (b) flow out through one or moreconduits connected to the vault 112, (c) evaporate and be carried intothe external atmosphere 122 by the manhole event suppression system 140,and (d) be pumped out by the vault owner. Depending upon theimplementation details, the System Controller 190 may not able todetermine an amount of the water being pumped from the vault 112 becausedoing so generally requires the removal of the manhole cover 144.

However, the System Controller 190 may utilize the method 800 tocalculate an amount of the water leaving the vault 112 by evaporation inthe evaporation flow F_(V). In first block 810, the System Controller190 obtains the component mass flow rate “w_(e)” of water vapor (seefifth row of rightmost column of Table B above) in the exhaust flowF_(E), the component mass flow rate “w_(f)” of water vapor (see fifthrow of rightmost column of Table C above) in the fresh air flow F_(FA),and the component mass flow rate “w_(c)” of water vapor (see fifth rowof fourth column of Table B above) in the connection(s) flow F_(C).

Then, in block 820, the System Controller 190 calculates the rate of netwater removal “Δw” by subtracting the component mass flow rate “w_(f)”and the component mass flow rate “w_(C)” from the component mass flowrate “w_(e).” Active ventilation evaporates a great deal of water andtransports that water out of the vault 112 and into the atmosphere. Byway of non-limiting examples, the System Controller 190 may calculatethe rate of net water removal “Δw” in g/min, liter/hr, and/or liter/day.

Then, the method 800 terminates.

The water level sensor 214 may be used to determine a depth of the waterpresent on the floor 168 of the vault 112. In periods when there is noprecipitation, any decrease in the depth of the water beyond thatattributable to the evaporation flow F_(V) of evaporating water iscaused by water leaking/diffusing through the concrete and/or flowingout through the conduit(s) connected to the vault 112. The componentmass flow rate “w_(c)” may be a combination of water leaking/diffusingthrough the concrete and/or flowing out through the conduit(s) connectedto the vault 112. If the System Controller 190 knows the height ofconnections 118A-118J, the System Controller 190 can calculate how muchof the decrease in the depth of the water was caused by waterleaking/diffusing through the concrete and water flowing out through theconduit(s) connected to the vault 112. For example, the amount of waterleaking/diffusing through the concrete may be empirically modeled withseasonal considerations. Also, visual or infrared cameras may be used toobserve water flowing through the conduit(s), and, where it issignificant, the System Controller 190 may use this information toestimate an amount of water flowing out through the conduit(s) connectedto the vault 112.

On the other side of the coin, the depth of the water can only increaseby one of four analogous mechanisms: (A) leak/diffuse through concrete,(B) flow in from conduit(s), (C) flow through the manhole cover whenthere is precipitation or (D) human induced irrigation. Human inducedirrigation may occur, for example, when city employees wish to enter astorm drain to conduct maintenance and pump water from the storm drainonto city streets. The water pumped from the storm drain flows down thestreet and enters the vault 112. The System Controller 190 may useweather data to determine when precipitation is occurring. During aprecipitation event, the System Controller 190 can monitor the increasein the depth of the water associated with the precipitation event andcreate a model of water ingress by precipitation rate and precipitationtype (e.g., rain, snow, etc.). If more water is entering the vault 112during a precipitation event than is desirable, the vault owner can takesteps to reduce this flow, such as checking that installation seals areproper, diverting run-off flow away from the manhole, and the like.

Dry vaults save their owners money. Vault owners have to pump out waterbefore entering their vaults and such water typically has to be disposedof as hazardous waste. Thus, it is desirable to keep the vaults dry asmuch as possible (e.g., for a greater portion of the year).Additionally, some industries, such as the U.S. nuclear industry,require that plant owners maintain dry vaults.

The System Controller 190 may use the time constant T to extrapolateinto the future. For example, if a CO₂ concentration sensor ispositioned on the north side of the vault 112 and a propane torch with aconstant burn rate is ignited on the south side of the vault 112, attime zero, the CO₂ concentration sensor has not yet detected any of theCO₂ produced by the propane torch. As time progresses, the CO₂concentration sensor detects more and more CO₂ produced by the propanetorch. The CO₂ produced by the propane torch will reach a plateau aftersome time. The plateau value of the CO₂ concentration is an indicationof the size of the fire. When the CO₂ concentration has reached itsplateau value, the System Controller 190 may determine the time constantT based on geometry of the vault 112 and the turnover rate calculated inblock 420 (see FIG. 11). The time constant τ (tau) is the quotient ofthe vault volume and the exhaust rate. For well mixed vaults (e.g.,where active ventilation is deployed) about 63.2% (i.e. 1−1/e) of acontaminant gas will be removed after one time constant. The turnoverrate may be either a rate of dilution of the first type or apredetermined fixed interchange rate. Thus, the System Controller 190may measure and/or calculate the time constant τ using the turnover rateand the geometry of the vault 112. Because the geometry of the vault 112is constant, the System Controller 190 may associate the time constant τwith the turnover rate. The next time the CO₂ concentration sensorbegins detecting an increase in the CO₂ concentration, the SystemController 190 may use the time constant τ associated with the currentturnover rate in the vault 112 to extrapolate the CO₂ concentrationdetected by the CO₂ concentration sensor to its future plateau value.Alternatively, the System Controller 190 may set the rate of dilution ofthe first type equal to the turnover rate and use the time constant T toextrapolate the CO₂ concentration detected by the CO₂ concentrationsensor to its future plateau value.

As mentioned above, the plateau value of the CO₂ concentration indicatesthe size of the fire. Thus, the System Controller 190 may determine thesize of a new propane fire shortly after the CO₂ concentration sensorbegins detecting an increase, rather than waiting for the asymptote tobe approached. In a real fire situation, this means quicker indicationof fire magnitude.

Each of the flows F_(E), O_(FFA), F_(C), and F_(V) include one or moregases. Typically, the exhaust flow F_(E) will include O₂, CO, CO₂, H₂O,and VOC. The fresh air flow F_(E) and the connection(s) flow F_(C) maycontribute any of these gases to the exhaust flow F_(E). However, theevaporation flow F_(V) may contribute only H₂O and/or VOC to the exhaustflow F_(E).

The System Controller 190 may obtain concentrations of O₂, CO, CO₂, H₂O,and/or VOC from third-party atmospheric data (e.g., www.aclima.io, whichprovides almost real time local data), dedicated sensors connectedwirelessly or via wired connections to the System Controller 190, or thefire detection sensor(s) 216 (see FIG. 3) where dilution of the secondtype is available. The System Controller 190 obtain the concentrationsof the components of the fresh air flow F_(FA) by using dilution of thesecond type to supply 100% fresh air to the fire detection sensor(s) 216(see FIG. 3). Then, the System Controller 190 simply obtains the sensorreadings from the fire detection sensor(s) 216 (see FIG. 3) and usesthem to determine the concentrations of the components of the fresh airflow F_(FA).

The methods 300, 350, 400, 500, 600, 700, and 800 as well as theequations described above are valid at steady state regardless of thesize of the underground vault 112.

In the case of an unventilated environment, sensor drift means that thefire detection sensor(s) 216 (see FIG. 3) cannot be relied upon and theSystem Controller 190 must make a trade-off between falsely alerting theowner of the underground vault 112 of a condition (a false positive) orsetting the alarm level at a dangerously high value and thus failing toalert the owner of a potentially dangerous condition (suffering falsenegatives). Various statistical methods can be used to optimize therequired trade-off between false positives and false negatives. Neitherfalse positives nor false negatives are desirable.

Some of these shortcomings can be overcome by using CalibrationlessOperation method 200 described above.

By way of non-limiting examples, any of the following may indicate afire:

-   -   i. CO₂ is elevated;    -   ii. CO is elevated;    -   iii. VOCs are elevated;    -   iv. H₂O (absolute humidity) is elevated;    -   v. NO is elevated;    -   vi. NO₂ is elevated;    -   vii. O₃ is elevated;    -   viii. SO₂ is elevated;    -   ix. O₂ is depressed (dilution by i-iv);    -   x. Temperature is elevated;    -   xi. Particulates are elevated; and/or    -   xii. H₂ is elevated.

Another non-limiting example of an alarm state may indicate thatflammable vapors are accumulating. By way of non-limiting examples, anyof the following conditions may indicate that flammable vapors areaccumulating:

-   -   i. CO is elevated;    -   ii. H₂ is elevated;    -   iii. VOCs are elevated; and/or    -   iv. H₂S is elevated.

Dilution by the System Controller

The System Controller 190 is configured to use an algorithm, heuristics,human input, and/or artificial intelligence to achieve the desiredmeasurements and to exercise the desired controls. Active and continuousventilation enjoys benefits beyond the primary purpose of explosionprevention. Non-limiting examples of such benefits include cooling anddrying the manhole environment, both of which contribute to improvedequipment reliability and life.

The System Controller 190 may control or throttle the exhaust rate overlimited periods of time for calibration purposes. The System Controller190 may calculate the time constants T (for associated turnover rates)for the underground vault 112, the time constants T the manhole eventsuppression system 140, and the time constants T for the two types ofdilution using methods that are well known in the art. Alternatively,the System Controller 190 may empirically deduce these time constants Tby throttling (to adjust the dilution of the first type) and by alteringthe IMR (to adjust the dilution of the second type). Non-limitingexamples of such purposeful dilution adjustments follow.

The System Controller 190 may frequently and automatically calibrate thefire detection sensor(s) 216 (see FIG. 3) utilizing one or more of thefollowing three tools:

-   -   1. a source of fresh air from the external atmosphere 122,    -   2. the ability to vary a ratio of exhausted air and the fresh        air, and    -   3. the ability to spike the fresh air with at least one pure        calibration gas (“cal-gas”).

The fresh air from the external atmosphere 122 may be used to dilute asample. For example, if an amount of a component gas of interest in asample (e.g., concentration of the component gas) approaches an upperlimit in the sensing range of a sensor, the System Controller 190 mayuse dilution of the first type and/or the second type to reduce theamount of the component gas of interest in the sample. Conversely, ifthe amount of the component gas of interest in the sample is at or belowa lower limit in the sensing range of the sensor, the System Controller190 may decrease dilution (at least temporarily) to increase the amountof the component gas of interest in the sample. In this way, the SystemController 190 may use dilution of the first type and/or the second typeto ensure the sensor is able to detect the amount of the component gasof interest by keeping the amount of the component gas of interestinside the sensor's sensing range.

If at least one flammable component gas is approaching an amount (e.g.,a concentration) that is dangerous (e.g., explosive or poisonous), theSystem Controller 190 may use dilution of the first type to reduce theamount of the at least one flammable component gas until the maximumexhaust flow rate is realized.

The System Controller 190 may calibrate one of the fire detectionsensor(s) 216 (see FIG. 3) by delivering to that sensor any IMR (zero toinfinity) of the exhaust flow F_(E) and fresh air from the exterioratmosphere 122. For example, the fresh air may contain about 21% oxygen.The System Controller 190 may direct the monitor 136 to supply an IMR ofzero, which includes 0% exhaust flow and 100% fresh air, to an oxygenconcentration sensor. Then, the System Controller 190 may calibrate theoxygen concentration sensor to 21%. Similarly, fresh air typically hasabout 400 ppm of carbon dioxide. The System Controller 190 may directthe monitor 136 to supply a ratio of zero, which includes 0% exhaustflow and 100% fresh air, to a carbon dioxide concentration sensor. Then,the System Controller 190 may calibrate the carbon dioxide concentrationsensor to 400 ppm.

Spiking is best implemented with materials that can be safety containedin liquid form, but are readily vaporized at temperature and pressureconditions found in the underground vault 112 (referred to as VaultTemperature and Pressure or “VTP”). Carbon dioxide, propane, and butaneare examples of materials that are safely and easily stored as liquids.Liquid spiking agents are preferred because a large volume of gas can begenerated from a relatively small volume of liquid. For example, theratio of gas volume (standard temperature and pressure or STP) to liquidvolume for carbon dioxide is about 390. Other gases of interest asspiking agents may not be easily liquefied and instead can be stored ashigh-pressure gases. Because a volume ratio of such gaseous spikingagents at VTP and at storage pressure is much less than the volume ratioof liquid spiking agents (e.g., an ideal gas such as oxygen at 2000 psihas a volume ratio of about 136, or roughly one-third of liquid carbondioxide), these gaseous spiking agents require larger containers, may beutilized less frequently, or must be periodically refilled or swapped.

It is not possible to calibrate a sensor with zero data points. A singledata point can be used for offset calibration. The shortcoming of thesingle point offset calibration is the slope of the response curve mayalso drift. A multi-point calibration is superior to a single pointcalibration because it allows adjustment of both the intercept and theslope of the calibration curve. More than two data points improve thecalibration further, but with diminishing returns. Non-limiting examplesof two-point calibration are provided in Table F (below). The SystemController 190 can calibrate one or more sensors using the informationof Table F:

TABLE F Gas Air Cal-gas CO₂ Assume 410 ppm in fresh air or use values~3-4% mixed with reported by air monitoring data suppliers fresh air COAssume 0 ppm in fresh air or use values 2 point calibration: reported byair monitoring data suppliers ~150 ppm and ~800 ppm (requires O₂ inmixture) O₂ Assume 20,900 ppm in fresh air or use 2 point calibration:values reported by air monitoring 2000 ppm and data suppliers 23000 ppmVOCs Assume 0 ppm in fresh air or use values 2 point calibration: (CH₄)reported by air monitoring data suppliers zero point and ~3-4% spike

When low concentration gases are encountered, the veracity of themeasurement can be tested by varying the dilution and/or immediatelyzero calibrating the relevant sensor(s). This is particularity useful toprevent false positives from errant sensors.

FIG. 16 illustrates a simplified network 900 of underground vaults 908(e.g., each like the vault 112) and underground connections 910 (e.g.,each like the connections 118A-118J). Each of the connections 910 may becharacterized as being an underground gas source. The network 900includes at least one monitor 912 (like the monitor 136 illustrated inFIG. 1) and the System Controller 190.

In FIG. 16, the vaults 908 include nine vaults A-1 to A-2, B-1 to B-3,and C-1 to C-3. One or more of the vaults 908 may house electricalequipment and/or electrical cables (e.g., like the electrical equipment119 of FIG. 1). Each of the vaults 908 may be characterized as being anode. Thus, FIG. 1 shows a simple nine-node network with two externalconnections Ext 01 and Ext 02. The external connection Ext 01 isconnected to the vault B-3 and the external connection Ext 02 isconnected to the vault C-2. Optionally, one or more of the vaults 908may include the manhole event suppression system 140.

In the embodiment illustrated, the connections 910 include connectionsAA12, AA23, BB12, BB23 a, BB23 b, CC12, CC23, AB11, AB22 a, AB22 b,AB33, BC11, BC22 a, BC22 b, and BC33. Each of the connections 910connects a pair of the vaults 908 together. For example, the connectionAA12 connects the pair of vaults A-1 and A-2 together. Each of theconnections 910 may be implemented as conduit, duct, or pipe. Some ofthe connections 910 include at least one cable that extendstherethrough. If a connection includes one or more cables, a gap may bedefined between the cable(s) and the connection. Such a gap providesfluidic communication between the connected vaults. Thus, a fluidic flowmay be present between the connected vaults. In some cases, a techniquereferred to as duct plugging, which involves installing a plug betweenthe cable(s) and the connection, may be used to limit such fluidic flow.Unfortunately, all such duct plugs are likely to leak after aging andespecially if a fire (oxidative decomposition, pyrolysis, and/orplasmatization) occurs and creates a positive pressure in the gapdefined between the cable(s) and the connection. Thus, generallyspeaking, the connections 910 allow at least some communication betweenthe vaults 908.

For ease of illustration, FIG. 16 omits connections (e.g., conduits)between building(s) owned by the vault owner's customers and one or moreof the vaults 908 and/or the connections 910. These connections provideelectrical and fluidic communication with one or more adjacent buildingsthat may serve as pathways for dangerous gases to enter customerpremises. Additionally, these connections may provide additional sourcesof undesirable gases inside the network 900.

The at least one monitor 912 has been illustrated as monitors 912A-912Ipositioned inside the vaults A-1 to A-2, B-1 to B-3, and C-1 to C-3,respectively. However, this is not a requirement. The network 900 mayinclude any number of monitors each like the monitors 912A-912Iinstalled in any of the vaults 908 and/or the connections 910.

The System Controller 190 communicates over wireless or wiredconnections with the monitors 912A-912I. The monitors 912A-912I are eachconfigured to send sensor data captured by the sensors 214 and 216 tothe System Controller 190. By way of a non-limiting example, the SystemController 190 may be implemented as a computing device 12 illustratedin FIG. 3 and described below.

FIG. 16 illustrates a fire 920 (oxidative decomposition, pyrolysis,and/or plasmatization) in the connection BB12 connecting the vaults B-1and B-2.

In this example, the fire detection sensor(s) 216 will be described asbeing implemented as chemical or gas concentration sensors. Such gasconcentration sensors are not defined and can utilize a variety ofphysical or chemical technologies, such as infra-red absorbance,florescence quenching, electro-chemical, thermal-conductivity, and/orflame ionization. Gases to be tested for the presence of at least oneanalyte are conveyed to the sensors (e.g., by tubing or ducting). Forthese types of sensors, which are each located in a single vault, todetermine where the fire 920 is located in the network 900, complicatedplumbing is required to draw gas from every possible source of theanalyte(s) of interest. For example, to determine which of theconnections AB11, BB12, and BC11 that exit from the vault B-1 harborsthe fire 920, the gases emanating from the connections AB11, BB12, andBC11 must be sampled independently by individual sets of sensors or aconveyance means must be used to convey a sample from each location to acentral sensor package. The conveyance means may include at least onetube, appropriate tubing connectors, at least one pump, and valvesactuated by the System Controller 190. The conveyance means delivers asample of gases collected from each of the connections AB11, BB12, andBC11 to the central sensor package.

While FIG. 16 illustrates the fire 920 (oxidative decomposition,pyrolysis, and/or plasmatization) occurring in the connection BB12, oneof ordinary skill in the art would recognize that the illustrated fireis only one of many possible sources of dangerous gases. Other sourcesinclude, but are not limited to, natural gas leaks from nearbypipelines, liquid-phase gasoline or diesel plumes, hydrogen sulfide, andvolatile organic compounds (VOCs) from biological decomposition.

When the manhole event suppression system 140 is deployed in each of thevaults 908, it is possible to narrow down the location of the offendingfire or gas source. The exhaust rates of the relevant manhole eventsuppression systems 140 may be set such that desired pressuredifferentials between the external and internal atmospheres 122 and 124(see FIG. 1) can be established. Then, a flow of one or more gasescreated by the fire 920 (or fire by-product(s)) into two or more thevaults 908 measured and used to determine where the fire 920 is located.For example, if the manhole event suppression systems 140 operating ineach of the vault B-1 and B-2 have about the same exhaust rates, thevault B-1 and B-2 have about the same negative pressure differentialbetween the external and internal atmospheres 122 and 124 (see FIG. 1).Thus, the flow rate of a first portion of the fire by-product(s) createdby the fire 920 flowing into the vault B-1 would be about twice that ofthe flow rate of a second portion of the fire by-product(s) flowing intothe vault B-2 because pneumatic resistance from the fire 920 to thevault B-1 is about half the pneumatic resistance from the fire 920 tothe vault B-2. Depending on the size of the fire 920, those of thevaults 908 adjacent to the vaults B-1 and B-2 may also experience smallincreases in the fire by-product(s), but these increases would beconsiderably less and considerably delayed by active ventilationgenerated by the manhole event suppression systems 140 in the vaults B-1and B-2 and a distance (e.g., several hundred feet) between the vaults.Thus, the relative concentrations of the analytes and their time ofarrival can be used to “triangulate” the connection that likely harborsthe fire 920 (or gas source) and determine the approximate location ofthe fire 920 (or gas source). When more than one of the connections 910joins two of the vaults 908 together, it may not be possible to identifythe connection harboring the fire 920 (or gas source), but connectionsto other vaults can be eliminated from consideration duringtroubleshooting.

Computing Device

FIG. 17 is a diagram of hardware and an operating environment inconjunction with which implementations of the System Controller 190 (seeFIGS. 1 and 3) may be practiced. The description of FIG. 17 is intendedto provide a brief, general description of suitable computer hardwareand a suitable computing environment in which implementations may bepracticed. Although not required, implementations are described in thegeneral context of computer-executable instructions, such as programmodules, being executed by a computer, such as a personal computer.Generally, program modules include routines, programs, objects,components, data structures, etc., that perform particular tasks orimplement particular abstract data types.

Moreover, those of ordinary skill in the art will appreciate thatimplementations may be practiced with other computer systemconfigurations, including hand-held devices, multiprocessor systems,microprocessor-based or programmable consumer electronics, network PCs,minicomputers, mainframe computers, and the like. Implementations mayalso be practiced in distributed computing environments (e.g., cloudcomputing platforms) where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed computing environment, program modules may be located inboth local and remote memory storage devices.

The exemplary hardware and operating environment of FIG. 17 includes ageneral-purpose computing device in the form of the computing device 12.The System Controller 190 (see FIGS. 1 and 3) may be substantiallyidentical to the computing device 12. By way of non-limiting examples,the computing device 12 may be implemented as a laptop computer, atablet computer, a web enabled television, a personal digital assistant,a game console, a smartphone, a mobile computing device, a cellulartelephone, a desktop personal computer, and the like.

The computing device 12 includes a system memory 22, the processing unit21, and a system bus 23 that operatively couples various systemcomponents, including the system memory 22, to the processing unit 21.There may be only one or there may be more than one processing unit 21,such that the processor of computing device 12 includes a singlecentral-processing unit (“CPU”), or a plurality of processing units,commonly referred to as a parallel processing environment. When multipleprocessing units are used, the processing units may be heterogeneous. Byway of a non-limiting example, such a heterogeneous processingenvironment may include a conventional CPU, a conventional graphicsprocessing unit (“GPU”), a floating-point unit (“FPU”), combinationsthereof, and the like.

The computing device 12 may be a conventional computer, a distributedcomputer, or any other type of computer.

The system bus 23 may be any of several types of bus structuresincluding a memory bus or memory controller, a peripheral bus, and alocal bus using any of a variety of bus architectures. The system memory22 may also be referred to as simply the memory, and includes read onlymemory (ROM) 24 and random access memory (RAM) 25. A basic input/outputsystem (BIOS) 26, containing the basic routines that help to transferinformation between elements within the computing device 12, such asduring start-up, is stored in ROM 24. The computing device 12 furtherincludes a hard disk drive 27 for reading from and writing to a harddisk, not shown, a magnetic disk drive 28 for reading from or writing toa removable magnetic disk 29, and an optical disk drive 30 for readingfrom or writing to a removable optical disk 31 such as a CD ROM, DVD, orother optical media.

The hard disk drive 27, magnetic disk drive 28, and optical disk drive30 are connected to the system bus 23 by a hard disk drive interface 32,a magnetic disk drive interface 33, and an optical disk drive interface34, respectively. The drives and their associated computer-readablemedia provide nonvolatile storage of computer-readable instructions,data structures, program modules, and other data for the computingdevice 12. It should be appreciated by those of ordinary skill in theart that any type of computer-readable media which can store data thatis accessible by a computer, such as magnetic cassettes, flash memorycards, solid state memory devices (“SSD”), USB drives, digital videodisks, Bernoulli cartridges, random access memories (RAMs), read onlymemories (ROMs), and the like, may be used in the exemplary operatingenvironment. As is apparent to those of ordinary skill in the art, thehard disk drive 27 and other forms of computer-readable media (e.g., theremovable magnetic disk 29, the removable optical disk 31, flash memorycards, SSD, USB drives, and the like) accessible by the processing unit21 may be considered components of the system memory 22.

A number of program modules may be stored on the hard disk drive 27,magnetic disk 29, optical disk 31, ROM 24, or RAM 25, including theoperating system 35, one or more application programs 36, other programmodules 37, and program data 38. A user may enter commands andinformation into the computing device 12 through input devices such as akeyboard 40 and pointing device 42. Other input devices (not shown) mayinclude a microphone, joystick, game pad, satellite dish, scanner, touchsensitive devices (e.g., a stylus or touch pad), video camera, depthcamera, or the like. These and other input devices are often connectedto the processing unit 21 through a serial port interface 46 that iscoupled to the system bus 23, but may be connected by other interfaces,such as a parallel port, game port, a universal serial bus (USB), or awireless interface (e.g., a Bluetooth interface). A monitor 47 or othertype of display device is also connected to the system bus 23 via aninterface, such as a video adapter 48. In addition to the monitor,computers typically include other peripheral output devices (not shown),such as speakers, printers, and haptic devices that provide tactileand/or other types of physical feedback (e.g., a force feed back gamecontroller).

The input devices described above are operable to receive user input andselections. Together the input and display devices may be described asproviding a user interface.

The computing device 12 may operate in a networked environment usinglogical connections to one or more remote computers, such as remotecomputer 49. These logical connections are achieved by a communicationdevice coupled to or a part of the computing device 12 (as the localcomputer). Implementations are not limited to a particular type ofcommunications device. The remote computer 49 may be another computer, aserver, a router, a network PC, a client, a memory storage device, apeer device or other common network node, and typically includes many orall of the elements described above relative to the computing device 12.The remote computer 49 may be connected to a memory storage device 50.The logical connections depicted in FIG. 17 include a local-area network(LAN) 51 and a wide-area network (WAN) 52. Such networking environmentsare commonplace in offices, enterprise-wide computer networks, intranetsand the Internet.

Those of ordinary skill in the art will appreciate that a LAN may beconnected to a WAN via a modem using a carrier signal over a telephonenetwork, cable network, cellular network, or power lines. Such a modemmay be connected to the computing device 12 by a network interface(e.g., a serial or other type of port). Further, many laptop computersmay connect to a network via a cellular data modem.

When used in a LAN-networking environment, the computing device 12 isconnected to the local area network 51 through a network interface oradapter 53, which is one type of communications device. When used in aWAN-networking environment, the computing device 12 typically includes amodem 54, a type of communications device, or any other type ofcommunications device for establishing communications over the wide areanetwork 52, such as the Internet. The modem 54, which may be internal orexternal, is connected to the system bus 23 via the serial portinterface 46. In a networked environment, program modules depictedrelative to the personal computing device 12, or portions thereof, maybe stored in the remote computer 49 and/or the remote memory storagedevice 50. It is appreciated that the network connections shown areexemplary and other means of and communications devices for establishinga communications link between the computers may be used.

The computing device 12 and related components have been presentedherein by way of particular example and also by abstraction in order tofacilitate a high-level view of the concepts disclosed. The actualtechnical design and implementation may vary based on particularimplementation while maintaining the overall nature of the conceptsdisclosed.

In some embodiments, the system memory 22 stores computer executableinstructions that when executed by one or more processors cause the oneor more processors to perform all or portions of one or more of themethods (including the method 200-A illustrated in FIG. 7A, the methods200-C to 200-W illustrated in FIGS. 7C-7W, and the method 300, 350, 400,500, 600, 700, and 800 illustrated in FIGS. 9, 10, 11, 12, 13, 14, and15, respectively) described above. Such instructions may be stored onone or more non-transitory computer-readable media.

In some embodiments, the system memory 22 stores computer executableinstructions that when executed by one or more processors cause the oneor more processors to generate the notifications identified in FIGS.7F-7H and described above. Such instructions may be stored on one ormore non-transitory computer-readable media.

The foregoing described embodiments depict different componentscontained within, or connected with, different other components. It isto be understood that such depicted architectures are merely exemplary,and that in fact many other architectures can be implemented whichachieve the same functionality. In a conceptual sense, any arrangementof components to achieve the same functionality is effectively“associated” such that the desired functionality is achieved. Hence, anytwo components herein combined to achieve a particular functionality canbe seen as “associated with” each other such that the desiredfunctionality is achieved, irrespective of architectures or intermedialcomponents. Likewise, any two components so associated can also beviewed as being “operably connected,” or “operably coupled,” to eachother to achieve the desired functionality.

While particular embodiments of the present invention have been shownand described, it will be obvious to those skilled in the art that,based upon the teachings herein, changes and modifications may be madewithout departing from this invention and its broader aspects and,therefore, the appended claims are to encompass within their scope allsuch changes and modifications as are within the true spirit and scopeof this invention. Furthermore, it is to be understood that theinvention is solely defined by the appended claims. It will beunderstood by those within the art that, in general, terms used herein,and especially in the appended claims (e.g., bodies of the appendedclaims) are generally intended as “open” terms (e.g., the term“including” should be interpreted as “including but not limited to,” theterm “having” should be interpreted as “having at least,” the term“includes” should be interpreted as “includes but is not limited to,”etc.). It will be further understood by those within the art that if aspecific number of an introduced claim recitation is intended, such anintent will be explicitly recited in the claim, and in the absence ofsuch recitation no such intent is present. For example, as an aid tounderstanding, the following appended claims may contain usage of theintroductory phrases “at least one” and “one or more” to introduce claimrecitations. However, the use of such phrases should not be construed toimply that the introduction of a claim recitation by the indefinitearticles “a” or “an” limits any particular claim containing suchintroduced claim recitation to inventions containing only one suchrecitation, even when the same claim includes the introductory phrases“one or more” or “at least one” and indefinite articles such as “a” or“an” (e.g., “a” and/or “an” should typically be interpreted to mean “atleast one” or “one or more”); the same holds true for the use ofdefinite articles used to introduce claim recitations. In addition, evenif a specific number of an introduced claim recitation is explicitlyrecited, those skilled in the art will recognize that such recitationshould typically be interpreted to mean at least the recited number(e.g., the bare recitation of “two recitations,” without othermodifiers, typically means at least two recitations, or two or morerecitations).

Conjunctive language, such as phrases of the form “at least one of A, B,and C,” or “at least one of A, B and C,” (i.e., the same phrase with orwithout the Oxford comma) unless specifically stated otherwise orotherwise clearly contradicted by context, is otherwise understood withthe context as used in general to present that an item, term, etc., maybe either A or B or C, any nonempty subset of the set of A and B and C,or any set not contradicted by context or otherwise excluded thatcontains at least one A, at least one B, or at least one C. Forinstance, in the illustrative example of a set having three members, theconjunctive phrases “at least one of A, B, and C” and “at least one ofA, B and C” refer to any of the following sets: {A}, {B}, {C}, {A, B},{A, C}, {B, C}, {A, B, C}, and, if not contradicted explicitly or bycontext, any set having {A}, {B}, and/or {C} as a subset (e.g., setswith multiple “A”). Thus, such conjunctive language is not generallyintended to imply that certain embodiments require at least one of A, atleast one of B, and at least one of C each to be present. Similarly,phrases such as “at least one of A, B, or C” and “at least one of A, Bor C” refer to the same as “at least one of A, B, and C” and “at leastone of A, B and C” refer to any of the following sets: {A}, {B}, {C},{A, B}, {A, C}, {B, C}, {A, B, C}, unless differing meaning isexplicitly stated or clear from context.

Accordingly, the invention is not limited except as by the appendedclaims.

1. A method comprising: obtaining a sensor reading from a sensor installed inside an underground vault; determining whether the sensor reading is indicative of an alarm state; when the sensor reading is indicative of the alarm state, obtaining multiple confirmatory measurements and determining whether the sensor reading includes sensor drift based at least in part on the multiple confirmatory measurements; establishing the alarm state when the sensor reading is determined not to include sensor drift; and removing the sensor drift when the sensor reading is determined to include sensor drift.
 2. The method of claim 1, wherein the confirmation measurements are obtained from the sensor.
 3. The method of claim 1, wherein the confirmation measurements are obtained from at least one corroborating sensor installed inside the underground vault or in at least one adjacent underground vault, the at least one corroborating sensor being different from the sensor.
 4. The method of claim 1, further comprising: notifying a user that the alarm state has been established.
 5. A method comprising: obtaining a sensor reading from a sensor installed inside an underground vault; determining whether the sensor reading is indicative of an alarm state; when the sensor reading is indicative of the alarm state, obtaining at least one new reading from at least one corroborating sensor and determining whether the sensor reading includes sensor drift based at least in part on the at least one new reading; establishing the alarm state when the sensor reading is determined not to include sensor drift; and removing the sensor drift when the sensor reading is determined to include sensor drift.
 6. The method of claim 5, further comprising: notifying a user that the alarm state has been established.
 7. A method comprising: obtaining a sensor reading from a sensor installed inside an underground vault; determining whether the sensor reading is indicative of an alarm state; if the sensor reading is indicative of the alarm state, triggering variable active dilution inside the underground vault, obtaining at least one new sensor reading after triggering the variable active dilution, and determining whether the sensor reading includes sensor drift based at least in part on the at least one new sensor reading; establishing the alarm state when the sensor reading is determined not to include sensor drift; and removing the sensor drift when the sensor reading is determined to include sensor drift.
 8. The method of claim 7, wherein the variable active dilution is dilution of a first type.
 9. The method of claim 7, wherein the variable active dilution is dilution of a second type.
 10. The method of claim 7, further comprising: notifying a user that the alarm state has been established.
 11. A system comprising: a sensor installed inside an underground vault; and a system controller comprising at least one processor connected to memory storing instructions executable by the at least one processor, the instructions, when executed by the at least one processor, causing the at least one processor to: obtain a sensor reading from the sensor; determine whether the sensor reading is indicative of an alarm state; when the sensor reading is indicative of the alarm state, obtain at least one new sensor reading and determine whether the sensor reading includes sensor drift based at least in part on the at least one new sensor reading; establish the alarm state when the sensor reading is determined not to include sensor drift; and remove the sensor drift when the sensor reading is determined to include sensor drift.
 12. The system of claim 11, wherein the at least one new sensor reading comprises one or more confirmation measurements obtained from the sensor.
 13. The system of claim 11, further comprising: at least one corroborating sensor installed inside the underground vault or in at least one adjacent underground vault, the at least one corroborating sensor being different from the sensor, the at least one new sensor reading comprising one or more confirmation measurements obtained from the at least one corroborating sensor.
 14. The system of claim 11, wherein when the sensor reading is indicative of the alarm state, the instructions, when executed by the at least one processor, cause the at least one processor to trigger variable active dilution inside the underground vault before obtaining the at least one new sensor reading.
 15. The system of claim 14, wherein the variable active dilution is dilution of a first type.
 16. The system of claim 14, wherein the variable active dilution is dilution of a second type.
 17. The system of claim 11, wherein the instructions, when executed by the at least one processor, cause the at least one processor to notify a user that the alarm state has been established.
 18. The system of claim 11, wherein the instructions, when executed by the at least one processor, cause the at least one processor to display a notification, on a display device, indicating the alarm state has been established.
 19. The system of claim 11, wherein the instructions, when executed by the at least one processor, cause the at least one processor to instruct an air moving device installed inside the underground vault to change an airflow rate after the alarm state has been established.
 20. The system of claim 19, wherein the airflow rate is increased after the alarm state has been established to increase thereby a turnover rate of an atmosphere inside the underground vault. 